1224 lines
156 KiB
Plaintext
1224 lines
156 KiB
Plaintext
Journal of Systems Architecture 160 (2025) 103365
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Contents lists available at ScienceDirect
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Journal of Systems Architecture
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journal homepage: www.elsevier.com/locate/sysarc
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Designing secure blockchain-based authentication and key management
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mechanism for Internet of Drones applications
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Mohammad Wazid a , Saksham Mittal a,b , Ashok Kumar Das c,d ,∗, SK Hafizul Islam e ,∗∗,
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Mohammed J.F. Alenazi f , Athanasios V. Vasilakos g
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a
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Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun 248 002, India
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b Department of Computer Science and Engineering, Graphic Era Hill University, Dehradun 248 002, India
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c Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad 500 032, India
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d Department of Computer Science and Engineering, College of Informatics, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, South Korea
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e
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Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani, West Bengal 741 235, India
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f
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Department of Computer Engineering, College of Computer and Information Sciences (CCIS), King Saud University, Riyadh 11451, Saudi Arabia
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g
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Center for AI Research (CAIR), University of Agder (UiA), 4879 Grimstad, Norway
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ARTICLE INFO ABSTRACT
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Keywords: Due to advancement in Information and Communications Technology (ICT) and Internet of Things (IoT), the
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Internet of Drones Internet of Drones (IoD) can be employed in numerous applications, facilitating the daily lives of diverse users,
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Blockchain including civilians and others. Wireless communication nature leads to an IoD environment to be vulnerable
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Authentication
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to various potential attack risks, such as data breaches, man-in-the-middle, impersonation, replay, and data
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Key agreement
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leaking attacks. As a result, the security of the IoD environment becomes crucial. To safeguard the data and
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Session key
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Security
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devices (such as IoT-enabled drones and servers) integral to IoD networks, a security solution is essential.
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It is imperative to implement targeted security measures, such as intrusion detection, access control, and
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authentication, in order to establish a security scheme that is both reliable and efficient. In this article, we
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mainly focus on developing a secure authentication and key management scheme that leverages blockchain
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technology. Most existing authentication techniques proposed in IoT and IoD environments are either inefficient
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in communication and computation, or they are insecure against various attacks. To mitigate these issues, this
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study proposes a secure blockchain-based authentication and key management scheme for IoD applications
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(in short BAKMM-IoD). The blockchain is applied here as a secure data storage purpose. After performing
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a detailed security analysis and formal security verification with the widely-recognized Scyther tool, the
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proposed BAKMM-IoD has exhibited resilience against different potential attacks. BAKMM-IoD also surpasses
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other contemporary existing schemes in terms of security and functionality features, including computational
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costs, and communication costs. Moreover, the blockchain simulation shows that the influence of the proposed
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BAKMM-IoD on critical performance metrics in real-world scenarios.
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1. Introduction This is a consequence of the accelerated pace at which technology
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is advancing. Drones are employed in various sectors, including en-
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Drones refer to unmanned aerial vehicles (UAVs) capable of au- vironmental monitoring, search and rescue operations during natural
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tonomous flight without the physical presence of a pilot or aviator. The disasters, and the oversight of ecologically sensitive regions, including
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term ‘‘unmanned aerial vehicles’’ (UAVs) specifically denotes drones. agricultural lands and forest fires [1]. The Internet of Drones (IoD) is a
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Drones are commonly battery-operated devices. In addition, their in- novel framework founded on the principles of the Internet of Things
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formation processing and storage capabilities are finite. The creation (IoT). Drones serve as replacements for physical objects inside this
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of energy-efficient and economical micro-controller designs has accel- framework.
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erated the progress of drone-based monitoring and control systems.
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∗ Corresponding author at: Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad 500 032, India.
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∗∗ Corresponding author.
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E-mail addresses: wazidkec2005@gmail.com (M. Wazid), mittalsaksham07@gmail.com (S. Mittal), iitkgp.akdas@gmail.com, ashok.das@iiit.ac.in (A.K. Das),
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hafi786@gmail.com, hafi786@iiitkalyani.ac.in (SKH Islam), mjalenazi@ksu.edu.sa (M.J.F. Alenazi), thanos.vasilakos@uia.no (A.V. Vasilakos).
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https://doi.org/10.1016/j.sysarc.2025.103365
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Received 13 November 2024; Received in revised form 12 January 2025; Accepted 6 February 2025
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Available online 15 February 2025
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1383-7621/© 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
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IoT has enhanced communication and interaction among drones, en- 1.3. Research contributions
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abling remote control in scenarios where direct optical transmission is
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impractical. An additional element of the IoD is the onboard controller, The following list outlines the research contributions made in this
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which employs artificial intelligence to make robust decisions [2– article.
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4]. IoD has various applications as discussed earlier. Cybersecurity
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concerns confronting the IoD. Some of them are as follows. Instances of • A secure blockchain-based authentication and key management
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data theft occur when adversaries illicitly intercept conversations and mechanism is proposed for IoD applications (in short, we call it
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pilfer data, including control and command signals that are utilized as BAKMM-IoD).
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to guide the drone [5]. Further, by exploiting vulnerabilities in drone • The proposed BAKMM-IoD has demonstrated to be secured against
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software, adversaries can remotely seize control of drones and hijack a wide range of potential threats after an extensive security
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them for their own objectives. Moreover, the faking of GPS signals analysis and formal verification utilizing the widely recognized
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by drones is facilitated by malicious software, therefore enabling their Scyther tool.
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use for harmful purposes. Apart from that unauthorized access to the • The BAKMM-IoD has been shown to surpass other similar contem-
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IoD systems can also be possible. An antagonistic user, such as an porary methods for functionality, security, computational over-
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attacker or hacker, can intercept the IoD network, enabling them to heads, and communication overheads.
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bypass it and execute man-in-the-middle (MiTM) attacks. Intercepting • A functional illustration of the proposed BAKMM-IoD is sub-
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the collected drone data is also feasible [5,6]. sequently shown to demonstrate its applicability to real-world
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settings.
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1.1. Potential ethical concerns belong to IoD communication
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2. Literature review
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Here, we discuss the key ethical concerns that belong to the IoD
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communication. It includes data sovereignty problems, because drones Authentication is one of the very important security services that
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operate across different borders may be from different countries or can be applied in various networking domains [13–19].
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states of a country, which potentially violates local laws (for exam- The safe authentication mechanism utilizing blockchain technology
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ple, the laws on data storage and its processing). Another potential
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was proposed by Yazdinejad et al. [20]. Drones were designed to
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challenge is ‘‘General Data Protection Regulation (GDPR)’’. It is the
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execute the planned deployment of the strategy in smart cities. At every
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European Union (EU) law that regulates how organizations handle
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stage of the process, this approach guaranteed the least amount of
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personal data [7]. It complies with the risk of unauthorized personal
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delays. A zone-based architecture was devised for a drone network, and
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data collection and excessive data processing [8]. IoD communication
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a decentralized consensus mechanism tailored for remote drone use in
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also faces concerns of data privacy, surveillance and accountability.
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smart cities was deployed.
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To address these issues and challenges, some of the strategies, such
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Bera et al. [21] introduced ACSUD-IoD, an innovative access control
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as data localization, privacy-by-design, use of strong encryption and
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system designed to identify and thwart unwanted unmanned aerial
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global regulatory standards, are necessarily needed [9].
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vehicles (UAVs) within the IoD. The storing of transactional data within
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a private blockchain framework was enabled by the integration of
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1.2. Research motivation
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a blockchain-based solution with ACSUD-IoD. This encompassed the
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While IoD fulfills various functions, enhancing the daily lives of a delivery of secure, standardized data from an UAV to the ground
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wide range of users and citizens, its communication framework is also station server. Consequently, the transactional data on the blockchain
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vulnerable to numerous risks, including data leakage, impersonation, is verifiable. A formal security verification was performed utilizing the
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replay, drone physical capture, stolen verifier attack, credentials/secret ‘‘Automated Validation of Internet Security Protocols and Applications
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keys/session keys leakage, Ephemeral Secret Leakage (ESL), malware (AVISPA) tool’’, alongside a comprehensive security evaluation. It il-
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injection and cross-site scripting attacks. The security of the IoD be- lustrated that their method was adequately protected against several
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comes vital, as it safeguards against numerous threats, including data possible threats.
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breaches, privacy infringements, and other security issues [10]. Pre- Feng et al. [22] proposed a ‘‘cross-domain authentication protocol
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ventive security measures can be adopted to alleviate these risks. grounded in blockchain technology’’. This system was designed to use
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Drones lacking robust cybersecurity protections are susceptible to nu- 5G technology for diverse IoD applications. The aforementioned limits
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merous risks. Therefore, to safeguard information and devices (includ- were duly acknowledged during the formulation of this plan with
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ing drones and servers) within IoD networks, a security mechanism the aim of transcending them. Their methodology was based on a
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is essential. Establishing a resilient security architecture requires the varied collection of signatures, all produced via threshold sharing. As
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deployment of particular security measures, such as authentication, a result, they successfully established a productive identity federation
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intrusion detection, and access control [11,12]. Moreover, the adoption for collaborative domains.
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of blockchain technology can bolster security against various potential Cho et al. [23] developed an authentication mechanism for un-
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threats and attacks [3]. manned aerial vehicles (UAVs) to reduce security threats linked to
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The security of blockchain technology stems from its decentral- unauthorized drones utilizing the IoD concept. Although their method-
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ized architecture and the application of encryption. Blockchains are ology reduced communication and computational requirements, yet
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decentralized networks that utilize a consensus (agreement) mecha- their architecture was vulnerable to the ‘‘Ephemeral Secret Leakage
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nism. Consequently, any effort to alter data can be identified by other (ESL) attack under the CK-adversary model’’. The method insufficiently
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nodes within the network. Blockchains employ cryptographic methods, protected the anonymity and untraceability of the participants. Another
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including public-key cryptography (i.e., ‘‘Elliptic Curve Cryptography element that contributed to this issue was the absence of blockchain
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(ECC)’’), to secure data and enable the generation of digital signatures. technology in their proposed strategy.
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This method protects data from unauthorized access and ensures its Gupta et al. [24] presented a GaRuDa system, which might po-
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confidentiality and integrity. Each data block in the chain is inher- tentially denoted as the drone-based delivery system that operated
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ently connected to the preceding and subsequent blocks to create an on the blockchain technology. The integration of this system into the
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immutable record of transactions. It is worth noticing that a block operations of Healthcare 5.0 applications was feasible. The IoT and
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is immutable and cannot be modified once it has been integrated blockchain technology were utilized in their approach to enable the
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into the chain [3]. In this article, we propose a secure blockchain- swift and accurate distribution of medical supplies, which could be
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based authentication and key management scheme that is applicable continuously monitored and recorded by many stakeholders. This was
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in various IoD-based real-life applications. achieved by using a 5G-enabled Internet environment.
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2
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M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
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A pair of unique communication strategies for UAV environments recognized as less secure compared to more robust alternatives like the
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were developed by Rodrigues et al. [25]. Their scheme facilitated the Secure Hash Algorithm (SHA-256). Consequently, the overall strength
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establishment of a direct exchange of messages between two drones. of their scheme is compromised. Moreover, their approach does not
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The presented scheme was derived from the existing scheme proposed incorporate support for blockchain implementation.
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in [26]. Nevertheless, the main contractual arrangement has been Research gaps and novelty: Blockchain technology offers powerful
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altered within the framework of this strategy. In accordance with solutions to strengthen the security of the IoD environment. By enabling
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the CK-adversary concept, their scheme was not impervious to the the creation of unique digital identities for individual drones, which
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possibility of an ESL attack. Moreover, their scheme lack support for are securely stored and managed on the blockchain, it helps mitigate
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the blockchain technology. the risk of impersonation attacks [37]. In addition, the data coming
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Ever [27] proposed an authentication system for IoT applications securely from the drones to the ground station server is used for
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that used Elliptic Curve Cryptography (ECC). UAVs were considered to the transactions and later, the blocks formed from the authentic and
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be mobile extensions of wireless sensor networks, operating within a hi- genuine data from the drones are stored in the blockchain network
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erarchical framework, according to their design. This particular design maintained by the cloud servers. Storing data on semi-trusted cloud
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enabled the effective implementation of one-time user authentication servers raises serious concerns about data poisoning attacks, which
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for mobile sinks (UAVs), cluster chiefs, and sensor nodes. In contrast, can significantly impact businesses and organizations by corrupting big
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their system was vulnerable to ‘‘ESL attack under the CK-adversary data analytics, leading to financial losses and reputational damage [38].
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model’’. Moreover, their scheme did not ensure the maintenance and Research shows notable improvements in accuracy, recall, precision,
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safeguarding of anonymity and untraceability. Another limitation of and F1-score when data is free from poisoning attacks and is directly
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their scheme was absence of blockchain technology and it required sourced from the blockchain. In this context, authentication among
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more communication and computational costs. drones and other entities in the IoD environment becomes critical to
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Singh et al. [28] examined the evolution and potential applications ensure that genuine data is stored on the blockchain.
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of the Internet of Drones. The advanced development of this technology The literature review highlights that most existing authentication
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has generated several apprehensions, among which the degree of secu- techniques for IoT and IoD environments are either inefficient in terms
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rity offered by autonomous robots has always been a prominent issue. of communication and computation or vulnerable to various attacks.
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Hence, they emphasized the most urgent security vulnerabilities and This underscores the need for a reliable and secure authenticated key
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suggested that the most efficient approach to address these challenges agreement protocol to facilitate secure data aggregation at ground
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would be to adopt state-of-the-art blockchain technology. station servers in the IoD environment, with blockchain technology
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Xiong et al. [29] introduced a secure collaborative computing sys- providing enhanced secure storage. Therefore, the objective of this
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tem that implemented blockchain technology. They initially created a work is to develop a novel and secure blockchain-based authentica-
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lightweight blockchain framework that was specifically designed for tion and key management mechanism for IoD applications that is not
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‘‘Unmanned Aerial Vehicle (UAV) Ad-Hoc Networks (UANET)’’. Fur- only resistant to various attacks but also efficient in communication
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ther, they introduced an improved ‘‘Practical Byzantine Fault Tolerance and computational costs, making it suitable for real-world practical
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(PBFT)’’ consensus algorithm that was based on trust assessment. applications.
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Wang et al. [30] introduced a mutual authentication method that
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was both simple and effective, and it exclusively relied on one-way hash 3. System models
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algorithms and bitwise XOR operations. Additionally, the issue of a cen-
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tralized trusted authority (TA) was mitigated by blockchain technology. The system models which are related to the BAKMM-IoD are ex-
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The Real-or-Random model-based formal security analysis was em- plained below. Moreover, the details of the network model and the
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ployed. Further, an informal security proof was provided to prove the threat model are given below.
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security of their proposed authentication mechanism. Further, Wang
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et al. [31] introduced, ‘‘BSIF: Blockchain-Based Secure, Interactive, 3.1. Network model
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and Fair Mobile Crowdsensing’’ system. It was blockchain-based and
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was distinguished by its security, interactivity, and impartiality. These Fig. 1 illustrates the proposed BAKMM-IoD’s network model. This
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attributes were achieved through the integration of smart contracts scenario involves several users, cloud servers, ground station servers,
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and mobile devices. Yu et al. [32] presented a ‘‘Cross-domain Indus- and several drones. The significant versatility of this architecture al-
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trial IoT Based on Consortium Blockchain mechanism (CBDS) for the lows its application across various industries, including smart farming,
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security of Industrial Internet of Things (IIoT). Further, they intro- industrial automation and control, intelligent transportation systems
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duced consortium blockchain specifically to establish trust across IIoT (ITS), and healthcare, among others. The drones are connected to the
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domains. ground station servers, which are in turn connected to the cloud servers
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Srinivas et al. [33] developed an innovative authentication tech- through communication channels. The ground station servers can con-
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nique that was anonymous, lightweight, and relied on temporal cre- sistently store the necessary data. Drones do not encounter excessive
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dentials for Internet of Things (IoT)-based platforms. It was denoted workloads as a substantial portion of computationally expensive tasks
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as 𝑇 𝐶 𝐴𝐿𝐴𝑆. To enhance 𝑇 𝐶 𝐴𝐿𝐴𝑆, Ali et al. [34] developed an are managed by the ground station servers. The data gathered by the
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improved version of 𝑇 𝐶 𝐴𝐿𝐴𝑆, referred to as 𝑖𝑇 𝐶 𝐴𝐿𝐴𝑆 for the secure drones is relayed to ground station servers for further analysis and
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communication of IoD. use. The partial blocks generated by the ground station servers from
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Mishra et al. [35] represented a framework for managing authenti- the received data are subsequently transmitted to the corresponding
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cation and session keys using blockchain technology. This framework cloud-based servers.
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supported the integration of big data analytics capabilities for drones Upon receiving partial data blocks, the cloud servers utilize them
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that operate on networks beyond 5G applications. Through a compre- to reconstruct the complete block. The aforementioned blocks may
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hensive security examination and scyther tool-based formal security ultimately be incorporated into the blockchain, contingent upon the
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verification, they have proven their scheme secured against the wide successful completion of the consensus procedure. The peer-to-peer
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range of attacks. cloud server network (P2PCS) is responsible for maintaining the func-
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In 2024, Algarni and Jan [36] proposed a robust yet lightweight tionality of the blockchain. Due to the implementation of advanced
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security mechanism utilizing a fuzzy extractor and the MD5 (Message technologies and substantial resources, the P2PCS network’s cloud
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Digest 5) algorithm to authenticate all IoD participants and ensure servers have exceptional processing, communication, and storage ca-
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secure communication. However, the MD5 hash algorithm is widely pabilities. The prevailing opinion is that cloud servers are semi-trusted
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3
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M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
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Fig. 1. Network model of the BAKMM-IoD.
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network entities. Cyberattacks may compromise the communication and then secure protocols need to use strong encryption and authentic-
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occurring between drones, cloud servers, and ground station servers. ity mechanisms to ensure confidentiality and integrity. Replay attacks
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The integrity of these communications may be jeopardized by the must be prevented by the use of current timestamp values, and mutual
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potential adversary . To guarantee system security, it is imperative authentication should be done using digital signatures or certificates
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to employ security measures such as authentication and key man- which helps in establishing credibility between entities. In the case
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agement under the present conditions. Insufficient implementation of of the CK-adversary model, mitigation focuses primarily on ephemeral
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this security feature may render the devices and servers suscepti- key exchanges to derive session keys even if the short-term secrets are
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ble to hackers. Potential hazards encompass ‘‘malware injection at- compromised, since it extends the DY-model assumptions and supports
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tacks, unauthorized data access, data replay attacks, man-in-the-middle forward secrecy and session independence. Both models call for formal
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(MiTM) attacks, impersonation attacks, and unauthorized session key validation of the protocols with the automated validation tools, like
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estimation attacks’’. Scyther, to ensure that security properties are met. Following these
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strategies, cryptographic protocols will survive in environments against
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3.2. Threat model the DY and CK adversaries.
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may also physically capture a certain number of drones and
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The proposed BAKMM-IoD is constructed based on the following extract data from their memory using an advanced power analysis
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threat models and assumptions. method [41]. The collected information can be used to launch as-
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sociated attacks and formulate additional malevolent acts, including
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• The Dolev–Yao (DY) threat model, which is widely acknowledged impersonation efforts. The use of disguised session keys and creden-
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as the prevailing de-facto standard [39]. DY model states that two tials, together with privileged insider attacks, may be implemented
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unprotected entities can communicate with each other across an in these attacks. Cloud servers are regarded as semi-trusted entities
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open network, such as the Internet. Entities at endpoints that are within the network because of their role in maintaining and storing
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often deemed untrustworthy comprise drones and ground station system data. The registration authority (RA) of the control room, tasked
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servers. Communications transferred across an unsecured network with the registration of network entities, concurrently serves as the
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can be accessed, modified, or deleted by an adversary , irrespec-
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registration authority for the network. Moreover, it is expected that the
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tive of their active or passive status. The BAKMM-IoD is designed
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system’s security would be compromised if 𝑅𝐴 were compromised, so
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to counter many potential attacks. Examples of these attacks
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undermining the system’s overall integrity.
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encompass the ‘‘physical drone capture attack, the ephemeral
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secret leakage (ESL) attack, the secret data leakage attack, the
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4. BAKMM-IoD: The proposed BAKMM-IoD
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impersonation attack, the replay attack, the man-in-the-middle
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(MiTM) attack, among others’’.
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The proposed BAKMM-IoD is comprehensively described in this sec-
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• The proposed BAKMM-IoD has been designed with the Canetti
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tion. The BAKMM-IoD is a multifaceted process that includes registra-
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and Krawczyk (CK) substantial adversary model as a consider-
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tion, authentication and key establishment, key management, dynamic
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ation [40]. Currently, possesses comprehensive access to all
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device integration, and blockchain implementation.
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attributes related to the model DY. Furthermore, session states,
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In the proposed BAKMM-IoD, the drones are communicating enti-
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encompassing session keys and credentials linked to a particular
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ties, which collect various data through their inbuilt units, i.e., sensors.
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session, are obtained by .
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After this data collection they send their data to the connected ground
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The DY threat model and the CK adversary model focus on defending station servers in a secure way with the help of the proposed ‘‘au-
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against those adversaries who possess the ability to alter communica- thentication and key establishment phase’’. The ground station servers
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tion channels while the cryptographic primitives remain intact. In the create partial blocks from this received data and then send it to the
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DY model, the adversary can intercept, modify, and inject messages, connected cloud servers in a secure way with the help of the given
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4
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M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
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Table 1 4.1.2. Registration of ground station server 𝐸 𝑆𝑗
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Notations used in BAKMM-IoD.
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The registration of ground station server 𝐸 𝑆𝑗 is performed as fol-
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Notation Meaning lows.
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BAKMM-IoD Short name of the proposed mechanism
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An adversary • RSES1: First 𝑅𝐴 chooses the secret key and secret number of
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𝐷𝐸𝑖 , 𝐼 𝐷𝐷𝐸𝑖 , 𝑅𝐼 𝐷𝐷𝐸𝑖 𝑖th deployed drone, its identity 𝐸 𝑆𝑗 as 𝑘𝐸 𝑆𝑗 and 𝑆 𝑁𝐸 𝑆𝑗 . Then 𝑅𝐴 chooses its identity as 𝐼 𝐷𝐸 𝑆𝑗 .
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and pseudo-identity, respectively Further, it computes pseudo identity number of 𝐸 𝑆𝑗 as 𝑅𝐼 𝐷𝐸 𝑆𝑗 =
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𝐸 𝑆𝑗 , 𝐼 𝐷𝐸 𝑆𝑗 , 𝑅𝐼 𝐷𝐸 𝑆𝑗 𝑗th ground station server, its identity
|
||
ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐸 𝑆𝑗 ∥𝑘𝑅𝐴 ∥𝑘𝐸 𝑆𝑗 ∥𝑆 𝑁𝐸 𝑆𝑗 ) and temporal credentials
|
||
and pseudo-identity, respectively
|
||
𝐶 𝑆𝑘 , 𝐼 𝐷𝐶 𝑆𝑘 , 𝑅𝐼 𝐷𝐶 𝑆𝑘 𝑘th cloud server, its identity parameter as 𝑇 𝐶𝐸 𝑆𝑗 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐸 𝑆𝑗 ∥𝑘𝑅𝐴 ∥𝑘𝐸 𝑆𝑗 ∥𝑆 𝑁𝐸 𝑆𝑗
|
||
and pseudo-identity, respectively ∥𝑅𝑇 𝑆𝐸 𝑆𝑗 ), where 𝑅𝑇 𝑆𝐸 𝑆𝑗 is the registration timestamp value of
|
||
𝑅𝐴, 𝑘𝑅𝐴 The registration authority 𝐸 𝑆𝑗 . 𝑅𝐴 also generates a provisional temporary identification
|
||
(trusted entity), its secret key number for 𝐸 𝑆𝑗 as 𝑇 𝐼 𝑁𝐸 𝑆𝑗 , and a secret primary key for 𝐸 𝑆𝑗 and
|
||
and its pseudo-identity, respectively
|
||
cloud server 𝐶 𝑆𝑘 as 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 . Here, it is important to mention
|
||
𝑘𝐷𝐸𝑖 , 𝑘𝐸 𝑆𝑗 Private keys 𝐷𝐸𝑖 and 𝐸 𝑆𝑗
|
||
𝑆 𝑁𝑅𝐴 , 𝑆 𝑁𝐷𝐸𝑖 and 𝑆 𝑁𝐸 𝑆𝑗 The secret numbers of
|
||
that 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 are distinct for different ground station servers
|
||
𝑅𝐴, 𝐷𝐸𝑖 and 𝐸 𝑆𝑗 , respectively and cloud server. Then 𝑅𝐴 stores the registration information of
|
||
𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 primary secret key of both 𝐷𝐸𝑖 and 𝐸 𝑆𝑗 registered 𝐷𝐸𝑖 and its own information in its database/memory.
|
||
𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 primary secret key of both 𝐸 𝑆𝑗 and 𝐶 𝑆𝑘 • RSES2: Finally, 𝐸 𝑆𝑗 contains {{(𝑇 𝐼 𝐷𝐷𝐸𝑖 , 𝑅𝐼 𝐷𝐷𝐸𝑖 ) |𝑖 = 1, 2, …,
|
||
𝑇𝑥 Different timestamp values used 𝑛𝐷𝐸 }, 𝑇 𝐼 𝑁𝐸 𝑆𝑗 , 𝑅𝐼 𝐷𝐸 𝑆𝑗 , 𝑇 𝐶𝐸 𝑆𝑗 , (𝑀 𝑆𝐷𝐸1 −𝐸 𝑆𝑗 , 𝑀 𝑆𝐷𝐸2 −𝐸 𝑆𝑗 …,
|
||
𝑟𝑠𝑥 Different random secret values used
|
||
𝑀 𝑆𝐷𝐸𝑛 −𝐸 𝑆𝑗 ), 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 , ℎ(⋅)} in the region of its secured
|
||
𝛥𝑇 The allowed delay value to 𝐷𝐸
|
||
mitigate replay attack database, where 𝑛𝐷𝐸 represents the entire quantity of drones
|
||
ℎ(⋅) Cryptographic one-way hash deployed under ground station server 𝐸 𝑆𝑗 .
|
||
function utilized
|
||
𝑆 𝐾𝑎𝑖 ,𝑏𝑗 The session key obtained and established The registration phase of ground station server 𝐸 𝑆𝑗 is given in Table 3.
|
||
in between entities 𝑎𝑖 and 𝑏𝑗
|
||
∥ A concatenation computation
|
||
⊕ A bitwise exclusive-OR (𝑋 𝑂𝑅) computation
|
||
4.1.3. Registration of 𝐶 𝑆𝑘
|
||
The subsequent process is employed to register cloud server 𝐶 𝑆𝑘 .
|
||
|
||
‘‘key management phase’’. The cloud servers are the part of peer-to- • RSCS1: First 𝑅𝐴 chooses the secret key and secret number of
|
||
peer server network and does the task of blockchain implementation. 𝐶 𝑆𝑘 as 𝑘𝐶 𝑆𝑘 and 𝑆 𝑁𝐶 𝑆𝑘 . Then 𝑅𝐴 chooses its identity as 𝐼 𝐷𝐶 𝑆𝑘 .
|
||
Some of the cloud servers are also the miner nodes of the network and Further, it calculates the pseudo identity of 𝐶 𝑆𝑘 as 𝑅𝐼 𝐷𝐶 𝑆𝑘 =
|
||
ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐶 𝑆𝑘 ∥𝑘𝑅𝐴 ∥𝑘𝐶 𝑆𝑘 ∥𝑆 𝑁𝐶 𝑆𝑘 ) and temporal credentials
|
||
perform the task of blockchain mining with the help of the consensus
|
||
parameter as 𝑇 𝐶𝐶 𝑆𝑘 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐶 𝑆𝑘 ∥𝑘𝑅𝐴 ∥𝑘𝐶 𝑆𝑘 ∥𝑆 𝑁𝐶 𝑆𝑘
|
||
algorithm.
|
||
∥𝑅𝑇 𝑆𝐶 𝑆𝑘 ), where 𝑅𝑇 𝑆𝐶 𝑆𝑘 is the registration timestamp value of
|
||
The details of the used notations are provided in Table 1 The
|
||
𝐶 𝑆𝑘 .
|
||
following is a concise overview of the phases.
|
||
• RSCS2: Finally, 𝐶 𝑆𝑘 contains {{(𝑇 𝐼 𝑁𝐸 𝑆𝑗 , 𝑅𝐼 𝐷𝐸 𝑆𝑗 ) |𝑗 = 1, 2, …,
|
||
𝑛𝐸 𝑆 }, 𝑅𝐼 𝐷𝐶 𝑆𝑘 , 𝑇 𝐶𝐶 𝑆𝑘 , (𝑀 𝑆𝐸 𝑆1 −𝐶 𝑆𝑘 , 𝑀 𝑆𝐸 𝑆2 −𝐶 𝑆𝑘 , …,
|
||
4.1. Registration phase
|
||
𝑀 𝑆𝐸 𝑆𝑛 −𝐶 𝑆𝑘 ), ℎ(⋅)} in its secured database, where 𝑛𝐸 𝑆 is the
|
||
𝐸𝑆
|
||
total number of ground station servers deployed under cloud
|
||
In this phase, the registration authority (𝑅𝐴) is tasked with regis-
|
||
server 𝐶 𝑆𝑘 .
|
||
tering the entities, which comprise the drone (𝐷𝐸𝑖 ), the ground station
|
||
server (𝐸 𝑆𝑗 ), and the cloud server (𝐶 𝑆𝑘 ). Comprehensive information The registration phase of cloud server 𝐶 𝑆𝑘 is provided in Table 4.
|
||
is provided here.
|
||
4.2. Authentication phase
|
||
4.1.1. Registration of drone 𝐷𝐸𝑖
|
||
The drone 𝐷𝐸𝑖 ’s registration is performed as follows. This section provides a detailed description of the mutual authenti-
|
||
cation and key establishment mechanism between a drone (𝐷𝐸𝑖 ) and
|
||
• RSDI1: Initially, 𝑅𝐴 designates 𝑆 𝑁𝑅𝐴 as its confidential (secret) its associated ground station server (𝐸 𝑆𝑗 ). The following steps need to
|
||
number and 𝑘𝑅𝐴 as its confidential key. The pseudo identity is be executed:
|
||
subsequently computed as follows: 𝑅𝐼 𝐷𝑅𝐴 = ℎ(𝐼 𝐷𝑅𝐴 ∥𝑆 𝑁𝑅𝐴
|
||
• AKDDE1: The drone 𝐷𝐸𝑖 produces a new timestamp value repre-
|
||
∥𝑘𝑅𝐴 ). Subsequently, it designates 𝐼 𝐷𝐷𝐸𝑖 as the identifier for
|
||
sented as 𝑇1 and a random secret value denoted as 𝑟𝑠1 . Further, it
|
||
𝐷𝐸𝑖 , 𝑘𝐷𝐸𝑖 as the confidential key, and 𝑆 𝑁𝐷𝐸𝑖 as the confidential
|
||
estimates some values as 𝑀1 = ℎ(𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 ) ⊕
|
||
number. The pseudo identity of 𝐷𝐸𝑖 is then calculated by 𝑅𝐴 as
|
||
ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 ) and 𝑀2 = ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥
|
||
𝑅𝐼 𝐷𝐷𝐸𝑖 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐷𝐸𝑖 ∥𝑘𝑅𝐴 ∥𝑘𝐷𝐸𝑖 ∥𝑆 𝑁𝐷𝐸𝑖 ). It calculates
|
||
𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑇1 ). It then sends message 𝑀 𝑆 𝐺1
|
||
the temporal credentials parameter of 𝐷𝐸𝑖 using the formula
|
||
= {𝑇 𝐼 𝐷𝐷𝐸𝑖 , 𝑀1 , 𝑀2 , 𝑇1 } to 𝐸 𝑆𝑗 through open channel, which
|
||
𝑇 𝐶𝐷𝐸𝑖 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐷𝐸𝑖 ∥𝑘𝑅𝐴 ∥𝑘𝐷𝐸𝑖 ∥𝑆 𝑁𝐷𝐸𝑖 ∥𝑅𝑇 𝑆𝐷𝐸𝑖 ), where
|
||
is insecure in nature.
|
||
𝑅𝑇 𝑆𝐷𝐸𝑖 is the registration timestamp value of 𝐷𝐸𝑖 . It generates
|
||
• AKDDE2: At the arrival of 𝑀 𝑆 𝐺1 , 𝐸 𝑆𝑗 checks condition |𝑇1 − 𝑇1∗ |
|
||
𝑇 𝐼 𝐷𝐷𝐸𝑖 as a provisional temporary identity for 𝐷𝐸𝑖 . The reg-
|
||
≤ 𝛥𝑇 , where the ‘‘maximum transmission delay’’ is given by
|
||
istration data has subsequently been stored in the memory of
|
||
𝛥𝑇 and 𝑇1∗ is receiving time of 𝑀 𝑆 𝐺1 . Here, it is important
|
||
𝐷𝐸𝑖 .
|
||
to say that 𝛥𝑇 also denotes the expected time interval for the
|
||
• RSDI2: Finally, 𝐷𝐸𝑖 stores values {𝑇 𝐼 𝐷𝐷𝐸𝑖 , 𝑅𝐼 𝐷𝐷𝐸𝑖 , 𝑇 𝐶𝐷𝐸𝑖 , transmission delay/preset acceptable delay threshold value. If
|
||
𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 , ℎ(.)}. Here, it is important to mention that the condition holds, 𝐸 𝑆𝑗 then fetches the values of 𝑅𝐼 𝐷𝐷𝐸𝑖
|
||
𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 is the primary secret key of both 𝐷𝐸𝑖 and 𝐸 𝑆𝑗 , this and 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 from its memory which is corresponding to
|
||
key distinct for different drones. As we have different deployed the received 𝑇 𝐼 𝐷𝐷𝐸𝑖 . After that 𝐸 𝑆𝑗 computes ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥
|
||
𝐷𝐸𝑖 , where 𝑖 = 1, 2, …, 𝑛𝐷𝐸 , and 𝑛𝐷𝐸 is the number of deployed 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 ) = 𝑀1 ⊕ ℎ(𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 ). After 𝐸 𝑆𝑗
|
||
drones. computes 𝑀2′ = ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥
|
||
The above drone registration phase is also given in Table 2. 𝑇1 ). Then it checks if 𝑀2′ = 𝑀2 ? If it matches then 𝐷𝐸𝑖 is
|
||
|
||
5
|
||
M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
|
||
|
||
Table 2
|
||
Registration phase of drone 𝐷𝐸𝑖 .
|
||
𝑅𝐴 𝐷 𝐸𝑖
|
||
Generate 𝑆 𝑁𝑅𝐴 &𝑘𝑅𝐴 .
|
||
Compute 𝑅𝐼 𝐷𝑅𝐴 = ℎ(𝐼 𝐷𝑅𝐴 ∥𝑆 𝑁𝑅𝐴 ∥𝑘𝑅𝐴 ).
|
||
Generate 𝐼 𝐷𝐷𝐸𝑖 for 𝐷𝐸𝑖 ,
|
||
Generate 𝑘𝐷𝐸𝑖 &𝑆 𝑁𝐷𝐸𝑖 for 𝐷𝐸𝑖
|
||
Compute 𝑅𝐼 𝐷𝐷𝐸𝑖 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐷𝐸𝑖 ∥𝑘𝑅𝐴 ∥𝑘𝐷𝐸𝑖 ∥𝑆 𝑁𝐷𝐸𝑖 ),
|
||
𝑇 𝐶𝐷𝐸𝑖 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐷𝐸𝑖 ∥𝑘𝑅𝐴 ∥𝑘𝐷𝐸𝑖 ∥𝑆 𝑁𝐷𝐸𝑖 ∥𝑅𝑇 𝑆𝐷𝐸𝑖 ).
|
||
Generate 𝑇 𝐼 𝐷𝐷𝐸𝑖
|
||
Store {𝑇 𝐼 𝐷𝐷𝐸𝑖 , 𝑅𝐼 𝐷𝐷𝐸𝑖 , 𝑇 𝐶𝐷𝐸𝑖 , 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 , ℎ(.)}.
|
||
|
||
|
||
|
||
Table 3
|
||
Registration phase of ground station server 𝐸 𝑆𝑗 .
|
||
𝑅𝐴 𝐸 𝑆𝑗
|
||
Generate 𝑘𝐸 𝑆𝑗 , 𝑆 𝑁𝐸 𝑆𝑗 &𝐼 𝐷𝐸 𝑆𝑗 for 𝐸 𝑆𝑗 .
|
||
Compute 𝑅𝐼 𝐷𝐸 𝑆𝑗 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐸 𝑆𝑗 ∥𝑘𝑅𝐴 ∥𝑘𝐸 𝑆𝑗 ∥𝑆 𝑁𝐸 𝑆𝑗 ),
|
||
𝑇 𝐶𝐸 𝑆𝑗 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐸 𝑆𝑗 ∥𝑘𝑅𝐴 ∥𝑘𝐸 𝑆𝑗 ∥𝑆 𝑁𝐸 𝑆𝑗 ∥𝑅𝑇 𝑆𝐸 𝑆𝑗 ).
|
||
Generate 𝑇 𝐼 𝑁𝐸 𝑆𝑗 &𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 .
|
||
Store {{(𝑇 𝐼 𝐷𝐷𝐸 𝑖 , 𝑅𝐼 𝐷𝐷𝐸 𝑖 )|𝑖 = 1, 2, … , 𝑛𝐷𝐸 }, 𝑇 𝐼 𝑁 𝐸 𝑆 𝑗 , 𝑅𝐼 𝐷𝐸 𝑆 𝑗 ,
|
||
𝑇 𝐶 𝐸 𝑆 𝑗 , (𝑀 𝑆 𝐷𝐸 1 −𝐸 𝑆 𝑗 , 𝑀 𝑆 𝐷𝐸 2 −𝐸 𝑆 𝑗 ⋯ , 𝑀 𝑆 𝐷𝐸 𝑛 −𝐸 𝑆 𝑗 ), 𝑀 𝑆 𝐸 𝑆 𝑗 −𝐶 𝑆 𝑘 , ℎ(⋅)}
|
||
𝐷𝐸
|
||
|
||
|
||
|
||
|
||
Table 4
|
||
Registration phase of cloud server 𝐶 𝑆𝑘 .
|
||
𝑅𝐴 𝐶 𝑆𝑘
|
||
Generate 𝑘𝐶 𝑆𝑘 , 𝑆 𝑁𝐶 𝑆𝑘 &𝐼 𝐷𝐶 𝑆𝑘 for 𝐶 𝑆𝑘 .
|
||
Compute 𝑅𝐼 𝐷𝐶 𝑆𝑘 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐶 𝑆𝑘 ∥𝑘𝑅𝐴 ∥𝑘𝐶 𝑆𝑘 ∥𝑆 𝑁𝐶 𝑆𝑘 ),
|
||
𝑇 𝐶𝐶 𝑆𝑘 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐶 𝑆𝑘 ∥𝑘𝑅𝐴 ∥𝑘𝐶 𝑆𝑘 ∥𝑆 𝑁𝐶 𝑆𝑘 ∥𝑅𝑇 𝑆𝐶 𝑆𝑘 ).
|
||
Store {{(𝑇 𝐼 𝑁𝐸 𝑆𝑗 , 𝑅𝐼 𝐷𝐸 𝑆𝑗 )|𝑗 = 1, 2, … , 𝑛𝐸 𝑆 }, 𝑅𝐼 𝐷𝐶 𝑆𝑘 ,
|
||
𝑇 𝐶𝐶 𝑆𝑘 , (𝑀 𝑆𝐸 𝑆1 −𝐶 𝑆𝑘 , 𝑀 𝑆𝐸 𝑆2 −𝐶 𝑆𝑘 , … , 𝑀 𝑆𝐸 𝑆𝑛 −𝐶 𝑆𝑘 ), ℎ(⋅)}
|
||
𝐸𝑆
|
||
|
||
|
||
|
||
|
||
authenticated with 𝐸 𝑆𝑗 . Further, 𝐸 𝑆𝑗 produces a new timestamp
|
||
Table 5 offers a succinct overview of the authentication and key
|
||
value represented as 𝑇2 and a random secret value denoted as
|
||
establishment mechanism. The above employed method provides the
|
||
𝑟𝑠2 . It then computes 𝑀3 = ℎ(𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 ) ⊕
|
||
protection of the communication channel between drones and ground
|
||
ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑟𝑠2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 ) and a session key
|
||
stations from external influences and interception of information. This
|
||
𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 = ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥ ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥
|
||
is because the initially the channel between 𝐷𝐸𝑖 and 𝐸 𝑆𝑗 is insecure.
|
||
𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑟𝑠2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 )∥ 𝑇1 ∥ 𝑇2 ∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ).
|
||
However, after the mutual authentication between 𝐷𝐸𝑖 and 𝐸 𝑆𝑗 , both
|
||
After that it computes 𝑀4 = ℎ(𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 ∥ 𝑇1 ∥ 𝑇2 ∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ).
|
||
𝑛𝑒𝑤 and
|
||
the entities 𝐷𝐸𝑖 and 𝐸 𝑆𝑗 are able to establish a common session key
|
||
It generates a new temporary identity for 𝐸 𝑆𝑗 as 𝑇 𝐼 𝐷𝐷
|
||
𝑛𝑒𝑤
|
||
𝐸𝑖 𝑆 𝐾𝐷𝐸𝑖 ,𝐸 𝑆𝑗 (= 𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 ) which can now be used for encrypting the
|
||
computes 𝑀5 = 𝑇 𝐼 𝐷𝐷𝐸 ⊕ ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥
|
||
𝑖 data exchanged between them. In that way, no adversaries will be able
|
||
𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑇2 ). 𝐸 𝑆𝑗 then sends message 𝑀 𝑆 𝐺2 = {𝑀3 , 𝑀4 , 𝑀5 ,
|
||
to tamper with the data because the data is already being encrypted
|
||
𝑇2 } to 𝐷𝐸𝑖 through open channel.
|
||
with the established session key which is unknown to the adversary. For
|
||
• AKDDE3: At the arrival of 𝑀 𝑆 𝐺2 , 𝐷𝐸𝑖 checks condition |𝑇2 − 𝑇2∗ | protecting a communication channel from unauthorized access, we use
|
||
≤ 𝛥𝑇 , where 𝑇2∗ is receiving time of 𝑀 𝑆 𝐺2 . If it matches the ‘‘Advanced Encryption Standard (AES-256) symmetric encryption’’
|
||
then 𝐷𝐸𝑖 compute ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑟𝑠2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 ) for reducing the computational time required for a drone.
|
||
= 𝑀3 ⊕ ℎ(𝑅𝐼 𝐷𝐷𝐸𝑖 ∥𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥𝑇2 ). After that 𝐷𝐸𝑖 calculates
|
||
the session key as 𝑆 𝐾𝐷𝐸𝑖 ,𝐸 𝑆𝑗 = ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 4.3. Key management phase
|
||
𝑇1 )∥ ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑟𝑠2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 )∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑇1 ∥
|
||
𝑇2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ) and 𝑀4′ = ℎ(𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 ∥ 𝑇1 ∥ 𝑇2 ∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ). It This procedure is conducted to manage the keys shared by 𝐸 𝑆𝑗 and
|
||
then checks condition 𝑀4′ = 𝑀4 ? If it matches, 𝐸 𝑆𝑗 is authen- 𝐶 𝑆𝑘 . Upon the successful conclusion of this process, 𝐸 𝑆𝑗 and 𝐶 𝑆𝑘 will
|
||
ticated with 𝐷𝐸𝑖 and computed session key by 𝐷𝐸𝑖 is correct. securely transmit their data using the specifically generated session key
|
||
𝐷𝐸𝑖 then computes its new temporary identity as 𝑇 𝐼 𝐷𝐷 𝑛𝑒𝑤 =
|
||
𝐸𝑖 𝑆 𝐾𝐸 𝑆𝑗 ,𝐶 𝑆𝑘 .
|
||
𝑀5 ⊕ ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑇2 ). Further,
|
||
it computes a session key verifier by generating another fresh • AKDEC1: 𝐸 𝑆𝑗 starts communication and produces a new times-
|
||
timestamp value 𝑇3 , which is 𝑀6 = ℎ(𝑆 𝐾𝐷𝐸𝑖 ,𝐸 𝑆𝑗 ∥ 𝑇3 ). Here it is tamp value represented as 𝑇 𝑆1 and a random secret value denoted
|
||
important to mention that 𝑀6 is a session key verifier, with the as 𝑅𝑆1 . Then, it computes 𝑚1 = ℎ(𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑅𝑆1 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥
|
||
help of 𝑀6 , 𝐸 𝑆𝑗 can check whether 𝐷𝐸𝑖 has computed the correct 𝑇 𝑆1 )⊕ ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 ) and 𝑚2 = ℎ(ℎ(𝑅𝑆1 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥
|
||
session key or not. After that 𝐷𝐸𝑖 sends message 𝑀 𝑆 𝐺3 = {𝑀6 , 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 )∥ 𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 ). After these
|
||
𝑇3 } to 𝐸 𝑆𝑗 through open channel. many computations 𝐸 𝑆𝑗 sends message 𝑚𝑠𝑔1 = {𝑇 𝐼 𝑁𝐸 𝑆𝑗 , 𝑚1 , 𝑚2 ,
|
||
• AKDDE4: At the arrival of 𝑀 𝑆 𝐺3 , 𝐸 𝑆𝑗 checks condition |𝑇3 − 𝑇3∗ | 𝑇 𝑆1 } to 𝐶 𝑆𝑘 through the open channel.
|
||
≤ 𝛥𝑇 , where 𝑇3∗ is receiving time of 𝑀 𝑆 𝐺3 . If it holds 𝐸 𝑆𝑗 • AKDEC2: At the arrival of 𝑚𝑠𝑔1 , 𝐶 𝑆𝑘 checks condition
|
||
computes 𝑀6′ = ℎ(𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 ∥ 𝑇3 ) and checks a condition 𝑀6′ |𝑇 𝑆1 − 𝑇 𝑆1∗ | ≤ 𝛥𝑇 , where 𝑇 𝑆1∗ is receiving time of 𝑚𝑠𝑔1 . If it
|
||
= 𝑀6 ? In the event of a match, 𝐸 𝑆𝑗 presumes that the session satisfies, then 𝐶 𝑆𝑘 fetches 𝑅𝐼 𝐷𝐸 𝑆𝑗 , and 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 correspond-
|
||
key generated by 𝐷𝐸𝑖 is correct. In the following phase, both ing to received 𝑇 𝐼 𝑁𝐸 𝑆𝑗 . Then, 𝐶 𝑆𝑘 computes ℎ(𝑅𝑆1 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥
|
||
𝐷𝐸𝑖 and 𝐸 𝑆𝑗 establish the session key 𝑆 𝐾𝐷𝐸𝑖 ,𝐸 𝑆𝑗 (= 𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 ) 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 ) = 𝑚1 ⊕ ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥𝑇 𝑆1 ) and 𝑚′2
|
||
to facilitate the secure transmission of their data. = ℎ(ℎ(𝑟𝑠1 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 )∥ 𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥
|
||
|
||
6
|
||
M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
|
||
|
||
Table 5
|
||
Authentication and key establishment between 𝐷𝐸𝑖 and 𝐸 𝑆𝑗 .
|
||
𝐷 𝐸𝑖 𝐸 𝑆𝑗
|
||
Generate 𝑟𝑠1 &𝑇1 .
|
||
Compute
|
||
𝑀1 = ℎ(𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 ) ⊕ ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥
|
||
𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )
|
||
𝑀2 = ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑇1 ).
|
||
𝑀 𝑆 𝐺1 = {𝑇 𝐼 𝐷𝐷𝐸𝑖 , 𝑀1 , 𝑀2 , 𝑇1 }
|
||
⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖
|
||
(via open channel) ⃗
|
||
Check if |𝑇1 − 𝑇1∗ | ≤ 𝛥𝑇 ? If so
|
||
Fetch 𝑅𝐼 𝐷𝐷𝐸𝑖 &𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗
|
||
Compute
|
||
ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )
|
||
= 𝑀1 ⊕ ℎ(𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 ).
|
||
𝑀2′ = ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑇1 ).
|
||
Check if 𝑀2′ = 𝑀2 ? If so,
|
||
generate 𝑇2 &𝑟𝑠2
|
||
Compute
|
||
𝑀3 = ℎ(𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 )
|
||
⊕ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑟𝑠2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 )
|
||
𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 = ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥
|
||
ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥
|
||
𝑟𝑠2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 )∥ 𝑇1 ∥ 𝑇2 ∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ).
|
||
𝑀4 = ℎ(𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 ∥ 𝑇1 ∥ 𝑇2 ∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ).
|
||
𝑛𝑒𝑤
|
||
Generate 𝑇 𝐼 𝐷𝐷 𝐸𝑖
|
||
Compute
|
||
𝑛𝑒𝑤
|
||
𝑀5 = 𝑇 𝐼 𝐷𝐷 𝐸𝑖
|
||
⊕ ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥
|
||
𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑇2 ).
|
||
𝑀 𝑆 𝐺2 = {𝑀3 , 𝑀4 , 𝑀5 , 𝑇2 }
|
||
⃖(via
|
||
⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖
|
||
open channel)
|
||
Check |𝑇2 − 𝑇2∗ | ≤ 𝛥𝑇 ? If so,compute
|
||
ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑟𝑠2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 )
|
||
= 𝑀3 ⊕ ℎ(𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 ),
|
||
𝑆 𝐾𝐷𝐸𝑖 ,𝐸 𝑆𝑗 = ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥ ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥
|
||
𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑟𝑠2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 )∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑇1 ∥ 𝑇2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ),
|
||
𝑀4′ = ℎ(𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 ∥ 𝑇1 ∥ 𝑇2 ∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ).
|
||
Check if 𝑀4′ = 𝑀4 ? If so, compute
|
||
𝑛𝑒𝑤
|
||
𝑇 𝐼 𝐷𝐷 𝐸𝑖
|
||
= 𝑀5 ⊕ ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥
|
||
𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥ 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑇2 ).
|
||
Generate 𝑇3 & compute
|
||
𝑀6 = ℎ(𝑆 𝐾𝐷𝐸𝑖 ,𝐸 𝑆𝑗 ∥ 𝑇3 ).
|
||
𝑀 𝑆 𝐺3 = {𝑀6 , 𝑇3 }
|
||
⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖⃖
|
||
(via open channel) ⃗
|
||
Check |𝑇3 − 𝑇3∗ | ≤ 𝛥𝑇 ? If so,
|
||
compute 𝑀6′ = ℎ(𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 ∥ 𝑇3 )
|
||
Check 𝑀6′ = 𝑀6 ? If so,
|
||
Store session key 𝑆 𝐾𝐷𝐸𝑖 ,𝐸 𝑆𝑗 store session key 𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖
|
||
|
||
|
||
|
||
𝑇 𝑆1 ). Next, it checks 𝑚′2 = 𝑚2 ? In case, if it holds, 𝐶 𝑆𝑘 produces 𝑇 𝑆2 ) and updates 𝑇 𝐼 𝑁𝐸𝑛𝑒𝑤 𝑆𝑗
|
||
with odd 𝑇 𝐼 𝑁𝐸 𝑆𝑗 in its database for
|
||
a new timestamp value represented as 𝑇 𝑆2 and a random secret future use. Then, it generates another fresh timestamp value as
|
||
value denoted as 𝑅𝑆2 . After that, it computes 𝑚3 = ℎ(𝑅𝑆2 ∥ 𝑇 𝑆3 and computes 𝑚6 = ℎ(𝑆 𝐾𝐸 𝑆𝑗 ,𝐶 𝑆𝑘 ∥ 𝑇 𝑆3 ) and sends message
|
||
𝑇 𝐶𝐶 𝑆𝑘 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐸 𝑆𝑗 ∥ 𝑇 𝑆2 ) ⊕ ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 ∥𝑇 𝑆2 ) 𝑚𝑠𝑔3 = {𝑚6 , 𝑇 𝑆3 } to 𝐶 𝑆𝑘 via open channel.
|
||
and a session key as 𝑆 𝐾𝐶 𝑆𝑘 ,𝐸 𝑆𝑗 = ℎ(ℎ(𝑅𝑆2 ∥ 𝑇 𝐶𝐶 𝑆𝑘 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ • AKDEC4: At the arrival of 𝑚𝑠𝑔3 , 𝐶 𝑆𝑘 checks condition
|
||
𝑇 𝑆2 )∥ ℎ(𝑅𝑆1 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 )∥ 𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ |𝑇 𝑆3 − 𝑇 𝑆3∗ | ≤ 𝛥𝑇 , where 𝑇 𝑆3∗ is receiving time of 𝑚𝑠𝑔3 , if it
|
||
𝑇 𝑆1 ∥ 𝑇 𝑆2 ). Again, it computes 𝑚4 = ℎ(𝑆 𝐾𝐶 𝑆𝑘 ,𝐸 𝑆𝑗 ∥ 𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ holds then 𝐶 𝑆𝑘 computes 𝑚′6 = ℎ(𝑆 𝐾𝐸 𝑆𝑗 ,𝐶 𝑆𝑘 ∥ 𝑇 𝑆3 ) and checks
|
||
𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆2 ) and generates a new temporary identifica- 𝑚′6 = 𝑚6 ? If it matches 𝐶 𝑆𝑘 assumes that 𝐸 𝑆𝑗 has computed the
|
||
tion number for 𝐸 𝑆𝑗 as 𝑇 𝐼 𝑁𝐸𝑛𝑒𝑤 𝑆𝑘
|
||
. After that 𝐶 𝑆𝑘 computes 𝑚5 correct session key. After that, both 𝐸 𝑆𝑗 and 𝐶 𝑆𝑘 establish session
|
||
= 𝑇 𝐼 𝑁𝐸𝑛𝑒𝑤𝑆𝑗
|
||
⊕ ℎ(𝑅𝐼 𝐷 𝐸 𝑆𝑗
|
||
∥ ℎ(𝑅𝑆1 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 )∥ key 𝑆 𝐾𝐸 𝑆𝑗 ,𝐶 𝑆𝑘 (= 𝑆 𝐾𝐶 𝑆𝑘 ,𝐸 𝑆𝑗 ) for their secure data transmission.
|
||
𝑇 𝑆2 ). After these many computations, 𝐶 𝑆𝑘 sends message 𝑚𝑠𝑔2
|
||
= {𝑚3 , 𝑚4 , 𝑚5 , 𝑇 𝑆2 } to 𝐸 𝑆𝑗 through the open channel.
|
||
4.4. Dynamic device addition phase
|
||
• AKDEC3: At the arrival of 𝑚𝑠𝑔2 , 𝐸 𝑆𝑗 checks condition
|
||
|𝑇 𝑆2 − 𝑇 𝑆2∗ | ≤ 𝛥𝑇 , where 𝑇 𝑆2∗ is receiving time of 𝑚𝑠𝑔2 , if In this phase, we provide the facility of addition of a new drone to
|
||
it holds then 𝐸 𝑆𝑗 compute ℎ(𝑅𝑆2 ∥ 𝑇 𝐶𝐶 𝑆𝑘 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆2 ) the network. If we do not provide this phase, a new device (i.e., drone)
|
||
= 𝑚3 ⊕ ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 ∥𝑇 𝑆2 ) and the session cannot be added to the network. However, this procedure is essentially
|
||
key 𝑆 𝐾𝐸 𝑆𝑗 ,𝐶 𝑆𝑘 = ℎ(ℎ(𝑅𝑆2 ∥ 𝑇 𝐶𝐶 𝑆𝑘 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆2 )∥ ℎ(𝑅𝑆1 ∥ needed especially when we do the expansion of the network or the
|
||
𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 )∥ 𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 ∥ 𝑇 𝑆2 ). It requirements of the users increase even in the case of physical drones
|
||
again computes 𝑚′4 = ℎ(𝑆 𝐾𝐸 𝑆𝑗 ,𝐶 𝑆𝑘 ∥ 𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆2 ). capture attack by an adversary. It can be done using the following steps.
|
||
Then, it checks if 𝑚′4 = 𝑚4 ? If it matches, the computed session
|
||
key by 𝐸 𝑆𝑗 is considered to be correct. Further, 𝐸 𝑆𝑗 computes • DDA1: 𝑅𝐴 chooses identity for 𝐷𝐸𝑖𝜈 as 𝐼 𝐷𝐷𝜈 , its secret key
|
||
𝐸𝑖
|
||
𝑇 𝐼 𝑁𝐶𝑛𝑒𝑤
|
||
𝑆
|
||
= 𝑚5 ⊕ ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ ℎ(𝑅𝑆2 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 )∥ as 𝑘𝜈𝐷𝐸 and its secret number as 𝑆 𝑁𝐷
|
||
𝜈 . 𝑅𝐴 further
|
||
𝐸
|
||
computes
|
||
𝑘 𝑖 𝑖
|
||
|
||
|
||
7
|
||
M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
|
||
|
||
|
||
the pseudo identity of 𝐷𝐸𝑖𝜈 as 𝑅𝐼 𝐷𝐷 𝜈
|
||
𝐸𝑖
|
||
= ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐷 𝜈
|
||
𝐸𝑖
|
||
For the better understanding of the readers, the proposed BAKMM-
|
||
∥𝑘𝑅𝐴 ∥𝑘𝜈𝐷𝐸 ∥𝑆 𝑁𝐷 𝜈 ). It again computes the
|
||
𝐸𝑖
|
||
temporal credentials IoD is also explained through a process flow diagram, which is depicted
|
||
𝑖
|
||
𝜈 𝜈 𝜈
|
||
value of 𝐷𝐸𝑖 as 𝑇 𝐶𝐷𝐸 = ℎ(𝑅𝐼 𝐷𝑅𝐴 ∥𝐼 𝐷𝐷𝐸 ∥𝑘𝑅𝐴 ∥𝑘𝐷𝐸 ∥𝑆 𝑁𝐷𝐸 𝜈 𝜈 in Fig. 2. It provides the details of various activities and processes
|
||
∥𝑅𝑇 𝑆𝐷 𝜈 ), where 𝑅𝑇 𝑆𝑖 𝜈 𝑖 𝑖
|
||
is the registration timestamp value of
|
||
𝑖
|
||
𝐸𝑖 𝐷𝐸𝑖
|
||
of the proposed scheme. The activities like registration of drone, reg-
|
||
𝜈
|
||
𝐷𝐸𝑖 . It again generates a temporary identity for 𝐷𝐸𝑖 as 𝑇 𝐼 𝐷𝐷𝐸 . 𝜈
|
||
istration of ground station server, and registration of cloud server
|
||
𝑖
|
||
Then, the registration information has been stored in the memory are highlighted. After that, there is the execution of authentication
|
||
of 𝐷𝐸𝑖𝜈 . and key establishment between the drone and ground station server.
|
||
• DDA2: Finally, 𝐷𝐸𝑖𝜈 stores values {𝑇 𝐼 𝐷𝐷 𝜈 , 𝑅𝐼 𝐷𝜈 , 𝑇 𝐶 𝜈 ,
|
||
𝐸𝑖 𝐷𝐸𝑖 𝐷𝐸𝑖
|
||
Further, there is the execution of key management between the ground
|
||
𝑀 𝑆𝐷 𝜈 , ℎ(.)}. Here, it is important to mention that station server and cloud server. After that, there is the execution of the
|
||
𝐸𝑖 −𝐸 𝑆𝑗
|
||
𝑀 𝑆𝐷 𝜈 is the primary secret key of both 𝐷𝐸𝑖𝜈 and 𝐸 𝑆𝑗 , this blockchain formation phase.
|
||
𝐸𝑖 −𝐸 𝑆𝑗
|
||
key distinct for different drones. 𝑅𝐴 also shares the registration
|
||
information of 𝐷𝐸𝑖𝜈 with the deployed 𝐸 𝑆𝑗 s in a secure way. Remark 1. Here, we provide the importance of using the blockchain
|
||
technology instead of using a strong public-key encryption algorithm,
|
||
like RSA-2048 or others, for storing the encrypted data in a semi-trusted
|
||
4.5. Blockchain implementation phase cloud environment. In fact, Mitra et al. [38] interestingly investigated
|
||
the ‘‘impact on blockchain-based artificial intelligence (AI)/machine
|
||
During this step, we present the specifics of the blockchain. It is a learning (ML)-enabled big data analytics for cognitive IoT environ-
|
||
significant phase of the proposed mechanism. Note that ‘‘Elliptic Curve
|
||
ment’’. They argued that data poisoning attacks are a serious concern
|
||
Cryptography (ECC)’’ encryption is used to encrypt a transaction in a
|
||
when the data is simply stored in semi-trusted cloud storage in place
|
||
block with the help of the public key 𝐾 𝑈𝐸 𝑆𝑗 of the respective ground
|
||
of the blockchain, because they can significantly impact businesses
|
||
station server (𝐸 𝑆𝑗 ) so that only 𝐸 𝑆𝑗 can decrypt the data using its
|
||
and organizations, both financially and in terms of their reputation,
|
||
own private key. In this case, since block verification involves the veri-
|
||
particularly when the big data analytics rely on corrupted data. Their
|
||
fication of signature present in a block using the ‘‘Elliptic Curve Digital
|
||
comprehensive experimental results illustrate the impact of data poi-
|
||
Signature Algorithm (ECDSA)’’ for signature verification, we have ap-
|
||
soning attacks on an ML model when data is stored in cloud storage
|
||
plied the public-key based ECC encryption for protection of transactions
|
||
(i.e., outside of blockchain) versus in a blockchain (i.e., without data
|
||
(containing the crucial data in case of sensitive applications such as
|
||
poisoning). The findings reveal substantial performance improvements
|
||
healthcare and military).
|
||
in accuracy, recall, precision, and F1-score when the data remain free
|
||
The particulars are delineated using the following steps:
|
||
from poisoning attacks. This is true because the data residing into the
|
||
• BIP1: As discussed earlier, the ground station server 𝐸 𝑆𝑗 receives blockchain cannot be tampered when the transactions are added into
|
||
information 𝐼 𝑛𝑓𝐷𝐸𝑖 from a connected drone 𝐷𝐸𝑖 through the the blockchain through the consensus mechanism. Hence, though the
|
||
established session key 𝑆 𝐾𝐷𝐸𝑖 ,𝐸 𝑆𝑗 in a secure way. Then 𝐸 𝑆𝑗 blockchain implementation becomes little more costly as compared to
|
||
creates a partial block 𝑃 𝐵 𝐾𝐸 𝑆𝑗 from the received information simply putting encrypted data in semi-trusted cloud storage, we cer-
|
||
𝐼 𝑛𝑓𝐷𝐸𝑖 . First, 𝐸 𝑆𝑗 creates its public and private key pairs as tainly have various advantages not only for strengthening the security
|
||
{𝐾 𝑈𝐸 𝑆𝑗 , 𝐾 𝑆𝐸 𝑆𝑗 } through some public key cryptographic sys- of the system, but also for improving substantial performance in terms
|
||
tems, i.e., Elliptic Curve Cryptography (ECC) algorithm. It then of accuracy, recall, precision, and F1-score in big data analytics.
|
||
divides 𝐼 𝑛𝑓𝐷𝐸𝑖 into some transactions say 𝑡𝑟𝑥 = {𝑡𝑟1 , 𝑡𝑟2 , …, 𝑡𝑟𝑥 }.
|
||
Further, 𝐸 𝑆𝑗 encrypts 𝑡𝑟𝑥 with its public key 𝐾 𝑈𝐸 𝑆𝑗 to convert Remark 2. The identity is the original identity information of an entity
|
||
them into encrypted transactions, say 𝑇 𝑅𝑥 = 𝐸𝐾 𝑈𝐸 𝑆 (𝑡𝑟𝑥 ). The (i.e., drone, ground station server and cloud server), whereas to make
|
||
𝑗
|
||
partial block contains fields as follows 𝑃 𝐵 𝐾𝐸 𝑆𝑗 = {𝑂𝑊 𝐼𝐸 𝑆𝑗 , the communication anonymous we have used pseudo identity, due to
|
||
𝐾 𝑈𝐸 𝑆𝑗 , 𝑇 𝑅𝑥 , 𝑀 𝑇𝑟𝑜𝑜𝑡𝐸 𝑆 }, where 𝑂𝑊 𝐼𝐸 𝑆𝑗 is owner 𝐸 𝑆𝑗 ’s identity this mechanism the original identity of an entity is not revealed to the
|
||
𝑗
|
||
information and 𝑀 𝑇𝑟𝑜𝑜𝑡𝐸 𝑆 is the Merkle tree root value, which other entities of the network. The temporary identity is used to make
|
||
𝑗
|
||
is generated from all transactions. 𝐸 𝑆𝑗 then sends partial block the communication anonymous as well as untraceable. The temporary
|
||
𝑃 𝐵 𝐾𝐸 𝑆𝑗 to connected cloud server 𝐶 𝑆𝑙 with the help of the identity information is changed in each session, because in each session
|
||
established session key 𝑆 𝐾𝐸 𝑆𝑗 ,𝐶 𝑆𝑘 in a secure way. we have the provision of use of a new temporary identity. It helps us
|
||
to achieve the untraceability property for the exchanged data in every
|
||
• BIP2: After receiving 𝑃 𝐵 𝐾𝐸 𝑆𝑗 , 𝐶 𝑆𝑙 makes full block 𝐹 𝐵 𝐾𝐶 𝑆𝑙
|
||
session of the communications.
|
||
from it. 𝐹 𝐵 𝐾𝐶 𝑆𝑙 contains fields as 𝐹 𝐵 𝐾𝐶 𝑆𝑙 = {𝐵 𝐼 𝐷𝐹 𝐵 𝐾𝐶 𝑆 ,
|
||
𝑙
|
||
𝑅𝑁𝐹 𝐵 𝐾𝐶 𝑆 , 𝑇 𝑆 𝑉𝐹 𝐵 𝐾𝐶 𝑆 , 𝐻 𝑎𝑠ℎ𝐹 𝐵𝐾𝐶 𝑆 , 𝐻 𝑎𝑠ℎ𝐹 𝐵𝐾𝐶 𝑆 , 𝑂𝑊 𝐼𝐸 𝑆𝑗 ,
|
||
𝑙 𝑙 𝑙 𝑙−1
|
||
𝐾 𝑈𝐸 𝑆𝑗 , 𝑇 𝑅𝑥 , 𝑀 𝑇𝑟𝑜𝑜𝑡𝐸 𝑆 , 𝑆 𝑖𝑔 𝑛𝐹 𝐵𝐾𝐶 𝑆 }, where 𝐵 𝐼 𝐷𝐹 𝐵 𝐾𝐶 𝑆 , 5. Security analysis of BAKMM-IoD
|
||
𝑗 𝑙 𝑙
|
||
𝑅𝑁𝐹 𝐵 𝐾𝐶 𝑆 , 𝑇 𝑆 𝑉𝐹 𝐵 𝐾𝐶 𝑆 , 𝐻 𝑎𝑠ℎ𝐹 𝐵𝐾𝐶 𝑆 , 𝐻 𝑎𝑠ℎ𝐹 𝐵 𝐾𝐶 𝑆 , and
|
||
𝑙 𝑙 𝑙 𝑙−1 In this section, a security analysis of the proposed scheme (BAKMM-
|
||
𝑆 𝑖𝑔 𝑛𝐹 𝐵 𝐾𝐶 𝑆 are the block’s (𝐹 𝐵 𝐾𝐶 𝑆𝑙 ) identity information, a
|
||
𝑙 IoD) is provided. The BAKMM-IoD has been subjected to an infor-
|
||
random nonce value, the timestamp, the hash of the current
|
||
mal security analysis utilizing mathematical concepts, assumptions and
|
||
block, the hash of the preceding block, and the block’s signature
|
||
proofs. The BAKMM-IoD has been shown to be secure to ‘‘replay at-
|
||
𝐹 𝐵 𝐾𝐶 𝑆𝑙 .
|
||
tacks, man-in-the-middle (MiTM) attacks, impersonation attacks, priv-
|
||
• BIP3: Upon the completion of this process, 𝐶 𝑆𝑙 will disseminate ileged insider attacks, stolen verifier attacks, physical drone capture
|
||
𝐹 𝐵 𝐾𝐶 𝑆𝑙 via its peer-to-peer cloud server network. At this junc- attacks, ephemeral secret leakage (ESL) attacks, secret data leakage
|
||
ture, the appointed leader, referred to as 𝐶 𝑆𝑙′′ , will initiate a
|
||
attacks, and other similar attacks’’. These findings were obtained after
|
||
consensus over the just received block. To achieve this purpose,
|
||
performing formal security analysis.
|
||
the server (𝐶 𝑆𝑙′′ ) may employ the procedures of the standard
|
||
‘‘practical Byzantine Fault Tolerance (pBFT) method [21]’’. The
|
||
Proposition 1. The SBBDA-IoD protocol makes it impossible to execute a
|
||
block 𝐹 𝐵 𝐾𝐶 𝑆𝑙 is incorporated into the blockchain 𝐵 𝐶 𝐻𝐼 𝑜𝐷𝑖 at
|
||
replay attack.
|
||
the successful completion of the consensus process. The formed
|
||
blockchain 𝐵 𝐶 𝐻𝐼 𝑜𝐷𝑖 can be considered like a ‘‘consortium
|
||
blockchain’’. As it contains some private data, however, at the Proof. Different freshly generated timestamp values are used and then
|
||
same time some of the data should be available publicly as per verified at the other recipient’s end. The aforementioned timestamp
|
||
the raised requirements. values encompass values like 𝑇1 , 𝑇2 , 𝑇3 , 𝑇 𝑆1 , 𝑇 𝑆2 and 𝑇 𝑆3 . Successful
|
||
|
||
8
|
||
M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
|
||
|
||
|
||
|
||
|
||
Fig. 2. Process flow diagram of the proposed BAKMM-IoD.
|
||
|
||
|
||
completion of the timestamp verification process may result in accep- is not permitted to access the database [42]. As a consequence of this,
|
||
tance of the message by the recipient. Otherwise, it will be returned as BAKMM-IoD has afforded protection against privileged insider attacks
|
||
undeliverable. By employing condition checking, i.e., |𝑇𝑥 − 𝑇𝑥∗ | ≤ 𝛥𝑇 , and other threats of a similar nature. These risks include attempts to
|
||
and |𝑇 𝑆𝑥 − 𝑇 𝑆𝑥∗ | ≤ 𝛥𝑇 , where 𝑥 = 1, 2, 3, the BAKMM-IoD ensures impersonation attempts, and illegal session key computations. There-
|
||
the prevention of replay attacks. Consequently, the BAKMM-IoD is fore, due to its capabilities, the proposal BAKMM-IoD has the potential
|
||
safeguarded against any replay attacks. □ to reduce the impact of attacks carried out by privileged insiders. □
|
||
|
||
Proposition 4. The BAKMM-IoD is effectively safeguarded against the
|
||
Proposition 2. The primary objective of the BAKMM-IoD is to prevent stolen verifier attack.
|
||
man-in-the-middle and impersonation attacks.
|
||
Proof. A segment of the cloud server’s database, safeguarded from
|
||
unauthorized access, contains information related to parameters col-
|
||
Proof. The computation of exchanged messages involves the utilization
|
||
lected by various entities, including drones and ground station servers.
|
||
of several proprietary factors, including 𝑘𝐸 𝑆𝑗 , 𝑆 𝑁𝐸 𝑆𝑗 , 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ,
|
||
These traits are said to signify the secret information maintained on
|
||
𝑘𝐶 𝑆𝑘 , 𝑆 𝑁𝐶 𝑆𝑘 , 𝑘𝑅𝐴 , 𝑅𝑇 𝑆𝐶 𝑆𝑘 , 𝑅𝑇 𝑆𝐸 𝑆𝑗 , 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 , 𝑘𝐷𝐸𝑖 , and 𝑆 𝑁𝐷𝐸𝑖 . To
|
||
ground station servers and devices. To ensure that fact, numerous layers
|
||
the attacker , these discrete values are unknown. Under the present
|
||
of protection have been established. Access to the confidential values of
|
||
circumstances, it is not feasible for to make any changes in the
|
||
the entities is unattainable for due to imposed restrictions [43]. Al-
|
||
transmitted messages. Another important consideration is that is
|
||
though this mechanism remains functional, executing an attack on the
|
||
unable to produce completely fresh messages in the correct way. Hence,
|
||
BAKMM-IoD via the stolen verifier method or other related techniques
|
||
the BAKMM-IoD offers protection against attacks, like, impersonation
|
||
seem unfeasible. Consequently, the BAKMM-IoD is safeguarded against
|
||
tries and man-in-the-middle attempts. □
|
||
the stolen verifier attack. □
|
||
|
||
Proposition 3. The BAKMM-IoD demonstrates robustness in the face of Proposition 5. The BAKMM-IoD possesses the capacity to prevent the
|
||
privileged insider attacks. stolen drone attack.
|
||
|
||
Proof. The secret values of the entities from the 𝑅𝐴’s database, namely Proof. The suggested implementation of the BAKMM-IoD safeguards
|
||
𝑘𝐸 𝑆𝑗 , 𝑆 𝑁𝐸 𝑆𝑗 , 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 , 𝑘𝐶 𝑆𝑘 , 𝑆 𝑁𝐶 𝑆𝑘 , 𝑅𝑇 𝑆𝐶 𝑆𝑘 , 𝑅𝑇 𝑆𝐸 𝑆𝑗 , 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 , sensitive information by ensuring that it is not stored in an unencrypted
|
||
𝑘𝐷𝐸𝑖 , and 𝑆 𝑁𝐷𝐸𝑖 have been removed. It may be deduced from this that state within the drones’ memory. Moreover, should successfully
|
||
the authorized user who possesses insider privileges (i.e., ) and who apprehend a drone and subsequently execute an advanced power anal-
|
||
intends to cause harm to the entities (i.e., through a variety of attacks) ysis attack to get critical data from the drone’s memory, it would
|
||
|
||
9
|
||
M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
|
||
|
||
|
||
|
||
|
||
Fig. 3. SPDL snippet for the implemented role of DE in BAKMM-IoD.
|
||
|
||
|
||
constitute one of the most perilous scenarios possible [41]. Assuming persistent information, such as secret keys and identities. In BAKMM-
|
||
these conditions were satisfied, would possess solely the session key IoD, the session keys are computed as 𝑆 𝐾𝐸 𝑆𝑗 ,𝐷𝐸𝑖 = ℎ(ℎ(𝑇 𝐶𝐷𝐸𝑖 ∥ 𝑟𝑠1 ∥
|
||
and registration data of this particular drone, lacking access to any 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇1 )∥ ℎ(𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑟𝑠2 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ∥ 𝑇2 )∥ 𝑇1 ∥ 𝑇2 ∥
|
||
other secret information related to the other drones. Each session key 𝑅𝐼 𝐷𝐷𝐸𝑖 ∥ 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 ) and 𝑆 𝐾𝐶 𝑆𝑘 ,𝐸 𝑆𝑗 = ℎ(ℎ(𝑅𝑆2 ∥ 𝑇 𝐶𝐶 𝑆𝑘 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥
|
||
within the BAKMM-IoD is unique and exclusive. Every computation is 𝑇 𝑆2 )∥ ℎ(𝑅𝑆1 ∥ 𝑇 𝐶𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 )∥ 𝑅𝐼 𝐷𝐸 𝑆𝑗 ∥ 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 ∥ 𝑇 𝑆1 ∥
|
||
executed using a distinct set of parameters. The deduced session key 𝑇 𝑆2 ). These session keys are computed through the long-term secret
|
||
cannot be utilized to ascertain the session key for additional drones, as parameters consist of the secret keys (i.e., 𝑅𝐼 𝐷𝐷𝐸𝑖 , 𝑅𝐼 𝐷𝐸 𝑆𝑗 , and
|
||
such an action is infeasible. This clearly indicates that unauthorized 𝑅𝐼 𝐷𝐶 𝑆𝑘 , 𝑘𝐸 𝑆𝑗 , 𝑆 𝑁𝐸 𝑆𝑗 , 𝑀 𝑆𝐸 𝑆𝑗 −𝐶 𝑆𝑘 , 𝑘𝐶 𝑆𝑘 , 𝑆 𝑁𝐶 𝑆𝑘 , 𝑅𝑇 𝑆𝐶 𝑆𝑘 , 𝑅𝑇 𝑆𝐸 𝑆𝑗 ,
|
||
access to the remaining portions of the communication is severely 𝑀 𝑆𝐷𝐸𝑖 −𝐸 𝑆𝑗 , 𝑘𝐷𝐸𝑖 , and 𝑆 𝑁𝐷𝐸𝑖 ), and the short-term secret parameter
|
||
forbidden. As a result, the BAKMM-IoD is protected against the stolen take the form of random secrets (i.e., 𝑟𝑠1 , 𝑟𝑠2 , 𝑅𝑆1 , 𝑅𝑆2 ). This results
|
||
drone attack. □ in the generation of a new session key for a subsequent session.
|
||
Furthermore, these concealed values are unknown to . Consequently,
|
||
it is impractical for to precisely ascertain the session key. This
|
||
Proposition 6. The BAKMM-IoD is designed to provide anonymity and indicates that a cannot reliably forecast the session key in any
|
||
untraceability for the exchanged communications. measure. Consequently, the BAKMM-IoD demonstrates adequate in-
|
||
tegrity to endure the ephemeral secret leaking (ESL) attack within the
|
||
CK-adversary model. □
|
||
Proof. No personally identifiable information (i.e., identities of the
|
||
communicating entities) is sent in plain text within the BAKMM-IoD’s
|
||
architecture. It ensures the safeguarding of the privacy of every indi- 6. Formal security verification of presented BAKMM-IoD
|
||
vidual thus helps us to achieve the anonymity of each entity during the
|
||
This section presents the formal security verification of the BAKMM-
|
||
communication. Freshly generated timestamp values (i.e., ‘‘𝑇1 , 𝑇2 , 𝑇3 ,
|
||
IoD. In the context of the BAKMM-IoD’s security, the Scyther tool [44,
|
||
𝑇 𝑆1 , 𝑇 𝑆2 , 𝑇 𝑆3 , and 𝑟𝑠1 , 𝑟𝑠2 , 𝑅𝑆1 , 𝑅𝑆2 ’’) and randomly produced secret
|
||
45], and [46] has been rigorously employed. The tools, like, ProVerif
|
||
values (i.e., 𝑘𝐷𝐸𝑖 , 𝑘𝐸 𝑆𝑗 , 𝑘𝐶 𝑆𝑘 ) constitute the entirety of the information
|
||
and AVISPA are somewhat less robust than this one in terms of ver-
|
||
that is reciprocally shared. It causes the creation of distinct mes-
|
||
ifying and analyzing the security of a recently developed security
|
||
sages for different entities in distinct sessions. Due to this mechanism,
|
||
protocol. During its operation, the system utilizes the most advanced
|
||
the exchanged messages cannot be traced during the communication.
|
||
cryptographic assumptions. The secret key ensures that an opponent
|
||
Therefore, it can be considered that the proposed BAKMM-IoD achieves
|
||
will be incapable of decrypting the data unless they themselves
|
||
anonymity and untraceability properties during the exchange of the
|
||
possess it. The language employed throughout the implementation
|
||
messages. □
|
||
phase is ‘‘Security Protocol Descriptive Language (SPDL)’’. A unique
|
||
role is allocated to each communication party or entity in this particular
|
||
Proposition 7. The ephemeral secret leakage (ESL) attack is unable to situation. As a consequence of their roles, the entities undertake several
|
||
successfully target the BAKMM-IoD under the CK-adversary model. other functions, such as the transmission of messages and the reception
|
||
of replies. The ‘‘send’’ and ‘‘recv’’ methods facilitate the attainment of
|
||
these objectives. The scyther tool operates on the DY model, with nine
|
||
Proof. The proposed BAKMM-IoD calculates the session key by com- other adversarial models, containing the eCK model and the CK model.
|
||
bining dynamic information, such as random secret numbers, with The system utilizes tests that facilitate the execution of verifications
|
||
|
||
10
|
||
M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
|
||
|
||
|
||
|
||
|
||
Fig. 4. SPDL snippet for the implemented role of ES in BAKMM-IoD.
|
||
|
||
|
||
such as agreement, synchronization, weak agreement, and secrecy. Table 6
|
||
In the Scyther implementation of a cryptographic protocol, metrics Execution time (in milliseconds) under a server.
|
||
|
||
such as agreement, synchronization, and secrecy are crucial. These are Primitive Max. time (ms) Min. time (ms) Average time (ms)
|
||
critical attributes for assessing the security and integrity of the newly 𝑇ℎ 0.149 0.024 0.055
|
||
designed protocol. These can be described as follows. 𝑇𝑚𝑡𝑝 0.199 0.092 0.114
|
||
𝑇𝑒𝑐 𝑠𝑖𝑔𝑔 3.147 0.308 0.729
|
||
𝑇𝑒𝑐 𝑠𝑖𝑔𝑣 6.147 0.593 1.405
|
||
• Agreement: It guarantees that two parties (e.g., drone and ground
|
||
𝑇𝑠𝑒𝑛𝑐 0.008 0.002 0.003
|
||
station server) recognize their participation in a session for data 𝑇𝑠𝑑 𝑒𝑐 0.005 0.002 0.003
|
||
communication. They both concur on significant aspects, such 𝑇𝑒𝑐 𝑚 2.998 0.284 0.674
|
||
as keys, identities, and so forth. It mitigates impersonation or 𝑇𝑒𝑐 𝑎 0.002 0.001 0.002
|
||
man-in-the-middle (MiTM) attacks by ensuring that both parties 𝑇𝑏𝑝 7.951 4.495 4.716
|
||
are authentically communicating as intended. Additionally, it
|
||
confirms that the protocol accomplishes mutual authentication. Table 7
|
||
• Synchronization: It guarantees that the sequence of message Execution time (in milliseconds) under Raspberry PI 3.
|
||
exchanges occurs as anticipated. Messages cannot be replayed, Primitive Max. time (ms) Min. time (ms) Average time (ms)
|
||
dropped, or modified. It is crucial for a protocol to attain this 𝑇ℎ 0.643 0.274 0.309
|
||
property, as it depends on the freshness or sequencing of messages 𝑇𝑚𝑡𝑝 0.406 0.381 0.385
|
||
(i.e., for the prevention of replay attacks). Moreover, it confirms 𝑇𝑒𝑐 𝑠𝑖𝑔𝑔 5.175 2.480 2.597
|
||
that both parties are operating in the same session context. 𝑇𝑒𝑐 𝑠𝑖𝑔𝑣 9.728 4.701 4.901
|
||
𝑇𝑠𝑒𝑛𝑐 0.038 0.017 0.018
|
||
• Secrecy: It guarantees that confidential information, such as ses-
|
||
𝑇𝑠𝑑 𝑒𝑐 0.054 0.009 0.014
|
||
sion keys or random secret nonces/numbers, remains undisclosed. 𝑇𝑒𝑐 𝑚 4.532 2.206 2.288
|
||
These values must not be disclosed to any unauthorized individu- 𝑇𝑒𝑐 𝑎 0.021 0.015 0.016
|
||
als. It serves to safeguard against eavesdropping and unauthorized 𝑇𝑏𝑝 32.79 27.606 32.084
|
||
data breach attempts.
|
||
To securely validate the ‘‘authentication and key establishment
|
||
phase’’ of the proposed BAKMM-IoD, we analyze the two critical actions functionality attributes’’ have been conducted. The details are provided
|
||
associated with DE (for a drone) and ES (for a ground station server). below. The comparisons of different schemes including Ali et al. [34],
|
||
The importance of these roles is substantial. The SPDL code snippets Cho et al. [23], Rodrigues et al. [25], Ever [27], Bera et al. [21] and
|
||
required for simulating the functions of a drone (𝐷𝐸𝑖 ) and a ground Mishra et al. [35] and the BAKMM-IoD are given.
|
||
station server (𝐸 𝑆𝑗 ) are presented in Figs. 3 and 4. Further, Fig. 5, We have taken the results of MIRACL library [21], in which various
|
||
located beneath the claim, status, and comments sections, displays values of execution time (i.e., computation time) are given. The exe-
|
||
the outcomes of the BAKMM-IoD implementation. The obtained data cution time (in milliseconds) values for a server are given in Table 6.
|
||
confirmed that the BAKMM-IoD corresponds with the stated assertions. Further, the execution time (in milliseconds) values under Raspberry
|
||
Thus, the BAKMM-IoD provides protection against numerous possible PI 3 for a device (i.e., smart IoT device, drones) are given in 7. Here
|
||
threats. it is important to mention that the donations 𝑇ℎ , 𝑇𝑠𝑒𝑛𝑐 ∕𝑇𝑠𝑑 𝑒𝑐 , 𝑇𝑏𝑝 , 𝑇𝑓 𝑒 ,
|
||
𝑇𝑒𝑐 𝑎 , 𝑇𝑒𝑐 𝑚 , 𝑇𝑒𝑐 𝑠𝑖𝑔𝑔 , 𝑇𝑒𝑐 𝑠𝑖𝑔 𝑣 , and 𝑇𝑚𝑡𝑝 are taken for the time needed for
|
||
7. Comparative analysis the execution a ‘‘one-way cryptographic hash function’’, a ‘‘symmetric
|
||
key encryption/decryption (AES-128)’’, a ‘‘bilinear pairing’’, a ‘‘fuzzy
|
||
In this section, the comparisons and analysis have been done for extractor’’, an ‘‘elliptic curve point addition’’, an ‘‘elliptic curve point
|
||
the BAKMM-IoD and other similar schemes of the domain. The compar- multiplication’’, a ‘‘ECDSA generation’’, ‘‘ECDSA verification’’, and a
|
||
isons of the computation costs, communication costs and ‘‘security and ‘‘map to point’’, respectively. It is considered that 𝑇𝑓 𝑒 (≈ 𝑇𝑒𝑐 𝑚 ) [47].
|
||
|
||
11
|
||
M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
|
||
|
||
|
||
|
||
|
||
Fig. 5. Results of security verification using scyther tool.
|
||
|
||
|
||
7.1. Comparison of computation costs Table 8
|
||
Comparing different computation costs.
|
||
Scheme Smart device/Drone GSS/Server
|
||
For computation costs assessment, 𝑇ℎ , 𝑇𝑠𝑒𝑛𝑐 ∕𝑇𝑠𝑑 𝑒𝑐 , 𝑇𝑏𝑝 , 𝑇𝑓 𝑒 , 𝑇𝑒𝑐 𝑎 ,
|
||
𝑇𝑒𝑐 𝑚 , 𝑇𝑒𝑐 𝑠𝑖𝑔𝑔 , 𝑇𝑒𝑐 𝑠𝑖𝑔𝑣 , and 𝑇𝑚𝑡𝑝 are used to signify for the time needed Ali et al. [34] 18𝑇ℎ + 𝑇𝑓 𝑒 + 𝑇𝑠𝑒𝑛𝑐 7𝑇ℎ + 3𝑇𝑠𝑒𝑛𝑐 ∕𝑇𝑠𝑑 𝑒𝑐
|
||
≈ 7.868 ms ≈ 0.394 ms
|
||
to execute a ‘‘one-way cryptographic hash function’’, a ‘‘symmetric
|
||
Cho et al. [23] 2𝑇𝑒𝑐 𝑠𝑖𝑔𝑣 + 𝑇𝑠𝑑 𝑒𝑐 2𝑇𝑒𝑐 𝑠𝑖𝑔𝑔 + 𝑇𝑠𝑒𝑛𝑐
|
||
key encryption/decryption (AES-128)’’, a ‘‘bilinear pairing’’, a ‘‘fuzzy +10001𝑇ℎ +10001𝑇ℎ
|
||
extractor’’, an ‘‘elliptic curve point addition’’, an ‘‘elliptic curve point ≈ 3100.125 ms ≈ 551.516 ms
|
||
multiplication’’, a ‘‘ECDSA generation’’, ‘‘ECDSA verification’’, and a Rodrigues et al. [25] 9𝑇ℎ + 6𝑇𝑒𝑐 𝑚 9𝑇ℎ + 2𝑇𝑒𝑐 𝑚
|
||
≈ 16.509 ms ≈ 1.843 ms
|
||
‘‘map to point’’, respectively. It is assumed that 𝑇𝑓 𝑒 (≈ 𝑇𝑒𝑐 𝑚 ) [47].
|
||
Ever [27] 9𝑇ℎ + 2𝑇𝑏𝑝 + 6𝑇ℎ + 3𝑇𝑏𝑝 +
|
||
The computation cost values are calculated on the basis of values 2𝑇𝑚𝑡𝑝 + 3𝑇𝑒𝑐 𝑚 2𝑇𝑚𝑡𝑝 + 3𝑇𝑒𝑐 𝑚
|
||
given in Tables 6 and 7. The computation cost values for the BAKMM- ≈ 74.583 ms ≈ 16.728 ms
|
||
IoD are calculated 8𝑇ℎ ≈ 2.47 ms (for drone) and 8𝑇ℎ ≈ 0.44 ms for Bera et al. [21] 9𝑇ℎ + 2𝑇𝑠𝑒𝑛𝑐 ∕𝑇𝑠𝑑 𝑒𝑐 9𝑇ℎ + 2𝑇𝑠𝑒𝑛𝑐 ∕𝑇𝑠𝑑 𝑒𝑐
|
||
+2𝑇𝑒𝑐 𝑚 + 𝑇𝑒𝑐 𝑎 2𝑇𝑒𝑐 𝑚 + 𝑇𝑒𝑐 𝑎
|
||
(ground satiation server). From Table 8, it is clear that the BAKMM-IoD
|
||
≈ 7.405 ms ≈ 1.851 ms
|
||
has less computation costs than the other compared schemes, i.e., the Mishra et al. [35] 9𝑇ℎ 7𝑇ℎ
|
||
schemes of Cho et al. [23], Rodrigues et al. [25], Ever [27], and Algarni ≈ 2.78 ms ≈ 0.39 ms
|
||
and Jan [36], whereas it is very similar to the scheme of Ali et al. [34] Algarni and Jan [36] 𝑇𝑓 𝑒 + 14𝑇ℎ 6𝑇ℎ
|
||
and Mishra et al. [35]. ≈ 6.614 ms ≈ 0.33 ms
|
||
BAKMM-IoD 8𝑇ℎ 8𝑇ℎ
|
||
≈ 2.47 ms ≈ 0.44 ms
|
||
7.2. Comparison of communication costs
|
||
|
||
To compute the communication expenses, we have presumed the
|
||
terms ‘‘identity’’, ‘‘random number’’, and ‘‘elliptic curve point 𝑃 =
|
||
{𝑇 𝐼 𝐷𝐷𝐸𝑖 , 𝑀1 , 𝑀2 , 𝑇1 }, 𝑀 𝑆 𝐺2 = {𝑀3 , 𝑀4 , 𝑀5 , 𝑇2 }, 𝑀 𝑆 𝐺3 = {𝑀6 , 𝑇3 }.
|
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(𝑃𝑥 , 𝑃𝑦 ) ∈ 𝐸𝑞 (𝑎, 𝑏)’’, where the coordinates of 𝑃 are denoted as 𝑃𝑥 and
|
||
𝑃𝑦 , hash output, generated using the SHA-256 hashing algorithm, and If we calculate the sizes of these messages, this is estimated as |𝑀 𝑆 𝐺1 |
|
||
the timestamp are 160 bits, 160 bits, (160 + 160) = 320 bits, 256 bits, = 160 + 256 + 256 + 32 = 704 bits, |𝑀 𝑆 𝐺2 | = 256 + 256 + 256 + 32 = 800 bits,
|
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and 32 bits, respectively. We subsequently calculate communication and |𝑀 𝑆 𝐺3 | = 256+32 = 2880 bits, as a whole the communication of the
|
||
costs in terms of the bit count necessary for transmitting messages BAKMM-IoD becomes 704+ 800+ 288 = 1782 bits. The communication
|
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𝑀 𝑆 𝐺1 , 𝑀 𝑆 𝐺2 , and 𝑀 𝑆 𝐺3 . expenses of different schemes are presented in Table 9. The data in
|
||
In the authentication and key establishment process of drone 𝐷𝐸𝑖 Table 9 indicates that the communication cost of the BAKMM-IoD is
|
||
and the 𝐸 𝑆𝑗 three messages are exchanged, which are 𝑀 𝑆 𝐺1 = lower than that of the other examined schemes.
|
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12
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Fig. 6. Results of implementation of blockchain for the proposed BAKMM-IoD: effect on computational time.
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|
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|
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Fig. 7. Results of implementation of blockchain for the proposed BAKMM-IoD: effect on transactions per second (TPS).
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Table 9 distinct scenarios or cases (case-1, case-2 and case-3) were tested and
|
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Comparative study on communication costs. compared. This experiment was conducted on a Windows 64-bit 11 OS
|
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Scheme No. of messages Total cost (in bits) with an Intel(R) Core i5-8250U processor, running at up to 1800 MHz
|
||
Ali et al. [34] 3 3424 and 8 GB RAM. Open source Visual Studio Code of version 1.93 with
|
||
Cho et al. [23] 3 3968 Java was used for programming environment. For case-1, the drone
|
||
Rodrigues et al. [25] 4 3456
|
||
Ever [27] 6 5344
|
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deployment was 50, for case-2, drone deployment was 100 and for case-
|
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Bera et al. [21] 3 2368 3, it was 150. The five blocks in case-1, ten blocks in case-2 and fifteen
|
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Mishra et al. [35] 3 1792 blocks in case-3 were computed as well as committed. Four miner nodes
|
||
Algarni and Jan [36] 4 2784 (i.e., cloud servers over P2PCS network) were used concurrently. It was
|
||
BAKMM-IoD 3 1792 deployed, for 10 ground station servers in case-1, 20 in case-2, and 30
|
||
in case-3. The voting-based method is followed for making consensus
|
||
in association with the practical byzantine fault tolerance (pBFT) in
|
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7.3. Comparison of security and functionality attributes
|
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blockchain mining work. Such details of the current flow of the trans-
|
||
actions are covered under the blanket of the encrypted transaction. For
|
||
The juxtaposition of security and functionality attributes is pre-
|
||
example, the entity (communicating party) by which the information
|
||
sented in Table 10. Based on the comparison, it is evident that the
|
||
is transmitted, or the underlying logic. The cipher-text of each such
|
||
BAKMM-IoD offers superior security and additional functional features transaction depends on elliptic curve cryptography (ECC) algorithm. It
|
||
compared to the other schemes given by Ali et al. [34], Cho et al. [23], could be said that the amount of additional bits necessary to encode
|
||
Rodrigues et al. [25], Ever [27], Bera et al. [21], Mishra et al. [35], the data in the way described is equal to 640 bits which is (320 + 320)
|
||
and Algarni and Jan [36]. bits. Encryption is done in every block to assess transactions worth 100.
|
||
The results following the simulations were determined as such.
|
||
8. Practical implementation of BAKMM-IoD: blockchain simula- There are other critical applications, where the data is strictly
|
||
tion confidential and private. Consider the healthcare applications using
|
||
the drones. Unmanned aerial vehicle (UAV) technology has greatly
|
||
The implementation of presented BAKMM-IoD is given here [48]. enriched the healthcare sector, making substantial contributions [49].
|
||
The details of the parameters that were used in the experimentation are As a result, drones are emerging as one of the fastest-growing technolo-
|
||
described in Table 11. During the experimentation and validation, three gies in the healthcare industry, offering a diverse array of applications.
|
||
|
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13
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M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
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|
||
Table 10
|
||
Comparison of security and functionality features.
|
||
Feature (𝐹 ) Ali et al. [34] Cho et al. [23] Rodrigues et al. [25] Ever [27] Bera et al. [21] Mishra et al. [35] Algarni and Jan [36] BAKMM-IoD
|
||
𝐴𝑆 𝐹 𝐹1 ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
|
||
𝐴𝑆 𝐹 𝐹2 ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
|
||
𝐴𝑆 𝐹 𝐹3 ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
|
||
𝐴𝑆 𝐹 𝐹4 ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
|
||
𝐴𝑆 𝐹 𝐹5 ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
|
||
𝐴𝑆 𝐹 𝐹6 ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
|
||
𝐴𝑆 𝐹 𝐹7 ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
|
||
𝐴𝑆 𝐹 𝐹8 ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
|
||
𝐴𝑆 𝐹 𝐹9 × × × × ✓ ✓ ✓ ×
|
||
𝐴𝑆 𝐹 𝐹10 × × × × ✓ ✓ × ✓
|
||
𝐴𝑆 𝐹 𝐹11 ✓ × × × ✓ ✓ × ✓
|
||
𝐴𝑆 𝐹 𝐹12 × × × × ✓ × × ✓
|
||
𝐴𝑆 𝐹 𝐹13 × × ✓ × ✓ ✓ × ✓
|
||
𝐴𝑆 𝐹 𝐹14 × × × × × × × ✓
|
||
|
||
𝐴𝑆 𝐹 𝐹1 : ‘‘protection for replay attack’’; 𝐴𝑆 𝐹 𝐹2 : ‘‘protection for man-in-the-middle attack’’; 𝐴𝑆 𝐹 𝐹3 : ‘‘availability of mutual authentication’’; 𝐴𝑆 𝐹 𝐹4 : ‘‘availability of
|
||
key agreement’’; 𝐴𝑆 𝐹 𝐹5 : ‘‘protection for device/drone impersonation attack’’; 𝐴𝑆 𝐹 𝐹6 : ‘‘protection for GSS/server impersonation attack’’; 𝐴𝑆 𝐹 𝐹7 : ‘‘protection for
|
||
malicious device deployment attack’’; 𝐴𝑆 𝐹 𝐹8 : ‘‘protection for drone/device physical capture attack’’; 𝐴𝑆 𝐹 𝐹9 : ‘‘formal security verification using AVISPA/Scyhter
|
||
tool’’; 𝐴𝑆 𝐹 𝐹10 : ‘‘protection for ESL attack under the CK-adversary model’’; 𝐴𝑆 𝐹 𝐹11 : ‘‘availability of dynamic drone/device addition phase’’; 𝐴𝑆 𝐹 𝐹12 :
|
||
‘‘implementation of blockchain’’; 𝐴𝑆 𝐹 𝐹13 : ‘‘availability of anonymity and untraceability properties’’; 𝐴𝑆 𝐹 𝐹14 : ‘‘availability of mechanism for secure communication
|
||
of ground station server and cloud server’’.
|
||
✓: ‘‘a scheme is secure or it supports an attribute’’; ×: ‘‘a scheme is insecure or it does not support an attribute’’.
|
||
|
||
|
||
Table 11 8.1. Effect on computational time
|
||
Simulation parameters and their values used in BAKMM-IoD.
|
||
Parameter Value The computation time values (in ms) were assessed to evaluate the
|
||
Platform used Windows 11 64 bit OS effect of a rising number of drones and ground station servers in each
|
||
Processor Intel (R) core (TM), scenario examined. The estimated computational times for case-1, case-
|
||
i5-8250U, 1600 MHz–1800 MHz
|
||
2, and case-3 are 9.12 ms, 17.88 ms, and 23.43 ms, respectively. The
|
||
RAM size 8 GB
|
||
Programming platform Visual studio code outcomes are also depicted in Fig. 6. The computational time escalates
|
||
v1.93 with Java with the growth in the number of drones and ground station servers
|
||
Quantity of deployed drones 50 (case-1), 100 (case-2), from case-1 to case-2 and from case-2 to case-3 due to the rise in the
|
||
150 (case-3) number of drones and ground station servers result in the generation
|
||
Quantity of ground station server 10 (case-1), 20 (case-2),
|
||
and incorporation of additional blocks (creation and mining) in the
|
||
30 (case-3)
|
||
Quantity of miner nodes 4 in all cases blockchain.
|
||
over P2P CS network
|
||
8.2. Effect on transactions per second (TPS)
|
||
|
||
These applications include real-time data collection, patient monitor- The effect of BAKMM-IoD on transactions per second (TPS) in the
|
||
ing, improved quality of care, and drug transportation. Hospitals are examined situations is measured. The transactions per second (TPS)
|
||
increasingly using drones to deliver medical supplies to remote and values are 54825, 55928 and 64103 for case-1, case-2 and case-3, re-
|
||
rural areas. Additionally, medical professionals are finding that drones spectively. The supplementary findings are depicted in Fig. 7. The
|
||
can enhance the accuracy of disease diagnoses. This technology has transactions value per second (TPS) on the blockchain escalates with
|
||
the potential to tackle some of the most pressing healthcare challenges, the augmentation of drones and ground station servers. This is the
|
||
such as providing medical assistance during disasters and transporting result of the production and incorporation (mining) of further blocks
|
||
organs for transplantation. entries to the blockchain.
|
||
Consider another sensitive application using the drones for battle-
|
||
field or military [50], where the data is also private and confidential. 9. Conclusions
|
||
The increasing adoption of UAVs in the defense and security sectors
|
||
for various purposes – including surveying, mapping, transportation, Security solutions are essential for safeguarding the data and de-
|
||
combat operations, and monitoring – is anticipated to drive demand vices, such as drones and servers, within IoD networks. A reliable
|
||
for military UAVs in the coming years. Additionally, the rise in defense blockchain-enabled authentication and key management mechanism
|
||
budgets across multiple countries aimed at acquiring modern and tech- for various IoD applications (BAKMM-IoD) was introduced. BAKMM-
|
||
nologically advanced military drones is expected to contribute to the IoD has been demonstrated to be secure against numerous potential
|
||
growth of the global market. threats through comprehensive security study and formal verification
|
||
For the simplicity of the implementation, the information which is with the widely recognized Scyther tool. BAKMM-IoD outperforms
|
||
used in the creation of the blocks, i.e., for the transactions field are like, other comparable current mechanisms regarding communication cost,
|
||
‘‘current temperature value for a particular location of region’’, ‘‘current calculation cost, and attributes of security and functionality. At the end,
|
||
humidity level for a particular location of a region’’. Likewise, we have a practical implementation of BAKMM-IoD is subsequently shown to
|
||
used various information in the transactions fields of a block. All these illustrate its applicability in real-world scenarios and highlight its effect
|
||
information are sent by the drones to the connected ground station on key performance metrics.
|
||
servers in a secure way with the help of the deployed ‘‘authentication In the future, we intend to provide machine learning/deep learning-
|
||
and key establishment phase’’. After that the ground station server based big data analytics phase in the presented scheme for the real-time
|
||
creates partial block from this information by putting this information data analysis of the received data. We have plan to provide a testbed
|
||
in the transaction field of the partial block. The transactions are en- implementation for the presented scheme. The post-quantum cryptog-
|
||
crypted (i.e., via Elliptic Curve Cryptography (ECC)-based encryption raphy (PQC)-based security primitives can also be incorporated in the
|
||
algorithm) since we need to provide the secrecy to the data. Please refer design of the presented scheme to make it more secure especially for
|
||
to the information given in Section 4.5. the era of quantum cryptography.
|
||
|
||
14
|
||
M. Wazid et al. Journal of Systems Architecture 160 (2025) 103365
|
||
|
||
|
||
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improved WBSN key-agreement protocol based on static parameters and hash plications (Elsevier), Computer Communications (Elsevier),
|
||
functions, IEEE Access 9 (2021) 78463–78473. International Journal of Communication Systems (Wiley),
|
||
[45] C.J.F. Cremers, Scyther : Semantics and verification of security protocols, Journal of Cloud Computing (Springer), Cyber Security
|
||
2006, https://pure.tue.nl/ws/files/2425555/200612074.pdf (Accessed on August and Applications (Elsevier), Alexandria Engineering Jour-
|
||
2024). nal (Elsevier), IET Communications, KSII Transactions on
|
||
[46] M. Tanveer, A.H. Zahid, M. Ahmad, A. Baz, H. Alhakami, LAKE-IoD: Lightweight Internet and Information Systems, and International Jour-
|
||
authenticated key exchange protocol for the internet of drone environment, IEEE nal of Communication Systems (Wiley). He also served as
|
||
Access 8 (2020) 155645–155659. one of the Technical Program Committee Chairs of the
|
||
[47] D. He, S. Zeadally, B. Xu, X. Huang, An efficient identity-based conditional first International Congress on Blockchain and Applications
|
||
privacy-preserving authentication scheme for vehicular ad hoc networks, IEEE (BLOCKCHAIN’19), Avila, Spain, June 2019, International
|
||
Trans. Inf. Forensics Secur. 10 (12) (2015) 2681–2691. Conference on Applied Soft Computing and Communica-
|
||
[48] M. Fan, X. Zhang, Consortium blockchain based data aggregation and regulation tion Networks (ACN’20), October 2020, Chennai, India,
|
||
mechanism for smart grid, IEEE Access 7 (2019) 35929–35940. second International Congress on Blockchain and Appli-
|
||
[49] Drones in healthcare: A lifesaving innovation, 2024, Available at: cations (BLOCKCHAIN’20), L’Aquila, Italy, October 2020,
|
||
https://www.indowings.com/blog/5-reasons-why-we-need-to-use-drones-in- and International Conference on Applied Soft Computing
|
||
the-hospital-management.php. (Accessed on October 2024). and Communication Networks (ACN’23), December 2023,
|
||
Bangalore, India. His Google Scholar h-index is 92 and
|
||
[50] Military drone market, 2023, https://www.fortunebusinessinsights.com/military-
|
||
i10-index is 302 with over 25,200 citations.
|
||
drone-market-102181. (Accessed on October 2024).
|
||
|
||
|
||
SK Hafizul Islam received the M.Sc. degree in applied
|
||
Mohammad Wazid received his Master of Technology in mathematics from Vidyasagar University, Midnapore, India,
|
||
Computer Network Engineering from Graphic Era Univer- in 2006, and the M.Tech. degree in Computer Application
|
||
sity, Dehradun, India, and received a Ph.D. in Computer and the Ph.D. degree in Computer Science and Engineering
|
||
Science and Engineering from the International Institute of in 2009 and 2013, respectively, from Indian Institute of
|
||
Information Technology, Hyderabad, India. He is currently Technology [IIT (ISM)] Dhanbad, Jharkhand, India, un-
|
||
working as a Professor in the Department of Computer der the INSPIRE Fellowship Ph.D. Program (funded by
|
||
Science and Engineering, Graphic Era University, Dehradun, the Department of Science and Technology, Government
|
||
India. He is the head of the cybersecurity and IoT research of India). He is currently an Assistant Professor in the
|
||
group at Graphic Era University, Dehradun, India. Prior to Department of Computer Science and Engineering, Indian
|
||
this, he was an assistant professor in the Department of Institute of Information Technology Kalyani (IIIT Kalyani),
|
||
Computer Science and Engineering at the Manipal Institute West Bengal, India. He has more than ten years of teaching
|
||
of Technology, MAHE, Manipal, India. He was also a post- and thirteen years of research experience. He has authored
|
||
doctoral researcher in the cyber security and networks lab, or co-authored 150 research papers in journals and con-
|
||
Innopolis University, Innopolis, Russia. His current research ference proceedings of international reputes. His research
|
||
interests include security, remote user authentication, the interests include Cryptography, Information Security, Neural
|
||
Internet of Things (IIoT), and cloud computing. He has Cryptography, Lattice-based Cryptography, IoT & Blockchain
|
||
published more than 100 papers in international journals Security, and Deep Learning. He has edited four books for
|
||
and conferences in the above areas. He was a recipient of the publishers Scrivener-Wiley, Elsevier, and CRC Press. He
|
||
the University Gold Medal and the Young Scientist Award is an Associate Editor for IEEE Transactions on Intelligent
|
||
from UCOST, the Department of Science and Technology, Transportation Systems, IEEE Access, International Journal
|
||
Government of Uttarakhand, India. He is a senior member of Communication Systems (Wiley), Telecommunication Sys-
|
||
of IEEE. tems (Springer), IET Wireless Sensor Systems, Security and
|
||
Privacy (Wiley), and Array - Journal (Elsevier). He is a
|
||
senior member of IEEE, and a member of ACM.
|
||
Saksham Mittal is pursuing Ph.D. CSE in the department
|
||
of CSE at Graphic Era Deemed to be University, Dehradun,
|
||
India. He is also associated with Graphic Era Hill University, Mohammed J.F. Alenazi earned his B.S., M.S., and Ph.D.
|
||
Dehradun, India as the teaching staff. His research inter- degrees in computer engineering from the University of
|
||
ests include intrusion detection systems, big data analytics, Kansas, USA, in 2010, 2012, and 2015, respectively. He is
|
||
threat analysis, and machine learning. a Professor in computer engineering at King Saud Univer-
|
||
sity and a reviewer for several international journals. His
|
||
research interests span cybersecurity, focusing on network
|
||
security, encryption, and vulnerability analysis, as well as
|
||
machine learning, where he applies AI to enhance network
|
||
security and performance. He also works on the design and
|
||
analysis of resilient networks, network routing, and mobile
|
||
Ashok Kumar Das, received a Ph.D. degree in computer
|
||
ad hoc network (MANET) protocols. A member of ACM, his
|
||
science and engineering, an M.Tech. degree in computer
|
||
work contributes to the intersection of cybersecurity and
|
||
science and data processing, and an M.Sc. degree in math-
|
||
machine learning for developing adaptive, threat-resistant
|
||
ematics from IIT Kharagpur, India. He is currently a full
|
||
systems.
|
||
Professor with the Center for Security, Theory and Algo-
|
||
rithmic Research, IIIT, Hyderabad, India. He is an adjunct
|
||
professor at the Korea University, Seoul, South Korea. He Athanasios V. Vasilakos is with the Center for AI Research
|
||
was also a visiting research professor with the Virginia (CAIR), University of Agder (UiA), Grimstad, Norway. He is
|
||
Modeling, Analysis and Simulation Center, Old Dominion WoS Highly Cited Researcher (HC), from 2016 to 2021. He
|
||
University, Suffolk, p=VA 23435, USA. His research inter- served or is serving as an Editor for many technical journals,
|
||
ests include cryptography, system and network security, such as the IEEE TRANSACTIONS ON NETWORK AND
|
||
blockchain, security in the Internet of Things (IoT), In- SERVICE MANAGEMENT, IEEE TRANSACTIONS ON CLOUD
|
||
ternet of Vehicles (IoV), Internet of Drones (IoD), smart COMPUTING, IEEE TRANSACTIONS ON INFORMATION
|
||
grids, smart city, cloud/fog computing, intrusion detection, FORENSICS AND SECURITY, IEEE TRANSACTIONS ON CY-
|
||
AI/ML security, and post-quantum cryptography. He has BERNETICS, IEEE TRANSACTIONS ON NANOBIOSCIENCE,
|
||
authored over 465 papers in international journals and IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY
|
||
conferences in the above areas, including over 395 re- IN BIOMEDICINE, ACM Transactions on Autonomous and
|
||
puted journal papers. He was a recipient of the Institute Adaptive Systems, and the IEEE JOURNAL ON SELECTED
|
||
Silver Medal from IIT Kharagpur. He has been listed in AREAS IN COMMUNICATIONS.
|
||
the Web of Science (ClarivateTM ) Highly Cited Researcher
|
||
2022 and 2023 in recognition of his exceptional research
|
||
performance. He is/was on the editorial board of IEEE
|
||
Transactions on Information Forensics and Security, IEEE
|
||
|
||
|
||
16
|
||
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