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All Journal Journal of Robotics and Control (JRC)
Al-Shareeda‬‏, ‪Mahmood A.
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Investigating Quantum-Resilient Security Mechanisms for Flying Ad-Hoc Networks (FANETs) Abbood, Abdulnasser AbdulJabbar; AL-Shammri, Faris K.; Alzamili, Zainab Marid; Al-Shareeda‬‏, ‪Mahmood A.; Almaiah, Mohammed Amin; AlAli, Rommel
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.25351

Abstract

Flying Ad Hoc Networks (FANETs) are indispensable in applications such as Surveillance, Disaster response missions, and Military operations. Both security and communication efficiency must meet certain requirements. However, their effectiveness is hobbled by dynamic topologies, resource constraints, and cyber threats. Therefore, Post-Quantum Cryptography (PQC) is necessary. Classical algorithms and current PQC schemes for FANETs have been discussed in this thesis, including cryptographic solutions that are lightweight enough for resourceconstrained environments. The numerical results of the experiment show that while lattice-based cryptography involves minimal risk of breaches, its power consumption is 25% higher than that for other systems and its processing time 30% slower. In contrast, multivariate polynomial cryptography is better on metrics like usage of electricity: only 10% more power consumed energywise and 15% more CPU cycles needed for processing. The introduction of PQC algorithms and architectures resulted in a 5–10% reduction in network throughput and increased latency to 20% in some scenarios. The results show that hybrid cryptographic systems—combining classical with PQC techniques— have the potential to achieve both high efficiency and long-term security. Case studies have validated the feasibility of tailored quantum-safe algorithms in FANETs, which can offer considerable security benefits while standing rigorous scrutiny in terms of scalability and computational performance on dynamic, missioncritical operations.
SECRE-MEN: A Lightweight Quantum-Resilient Authentication Framework for IoT-Edge Networks Faleh, May Adnan; Abdulsada, Ali M.; Alaidany, Ali A.; Al-Shareeda‬‏, ‪Mahmood A.; Almaiah, Mohammed Amin; Shehab, Rami
Journal of Robotics and Control (JRC) Vol. 6 No. 4 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i4.26006

Abstract

The wide 6G-IoT and Mobile Edge Computing (MEC) deployments give rise to severe concerns in authentication, revocation and protection against quantum-post and side channel attacks. In this paper, SECRE-MEN (Secure and Efficient Cryptographic Revocable Authentication for MEC enabled Networks) is presented to be a lightweight and scalable authentication architecture specifically designed for the resource limited IoT systems. SECRE-MEN consists of three main parts: (1) Masked Cryptographic Techniques that are used to randomise elliptic curve operations, thereby mitigate side-channel attacks, (2) VCs, providing support for digitally-signed, lightweight authentication, without requiring the use of bulky certificates, and (3) a Bloom filter-based RDB, which is distributed across multiple MEC nodes, to allow for fast, memory-efficient revocation checks. To enable future-proof security post-quantum cryptography (PQC) is included in SECRE-MEN by lattice-based schemes, such as Kyber and Dilithium, which may incur additional computational cost on ultra-low-power platforms according to the trade-off introduced in this paper. Effort experiments show that the proposed RAM-MENAMI decreases 29.3% the computation cost, and reduces 21.8% the communication budget and improve 20.3% of power efficiency in comparison with the RAM-MEN. In addition, SECRE-MEN is resistant against impersonation, MITM, replay and quantum attacks, as well as allows for dynamic revocation and secure synchronization among MEC nodes. This places SECREMEN as an effective toolkit for cybersecurity of massive IoT-MEC networks in the era of the evolving 6G.
Artificial Intelligence-Driven and Secure 5G-VANET Architectures for Future Transportation Systems Saare, Murtaja Ali; Abdulhamed, Mohamed Abdulrahman; Al-Shareeda‬‏, ‪Mahmood A.; Almaiah, Mohammed Amin; Shehab, Rami
Journal of Robotics and Control (JRC) Vol. 6 No. 4 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i4.26295

Abstract

The advent of 5G has opened a new era of intelligent, adaptive and secure VANETs that is envisaged to serve as the backbone network architecture for next generation of vehicular transportation systems. In this work, we present a connected 5G VANETs-to-Edge Computing systems with Artificial Intelligence (AI) infrastructure to improve system adaptability, anomaly detection, trust management, and real-time decisionmaking. Crucial enabling technologies like Software-Defined Networking (SDN). Mobile Edge Computing (MEC), and millimeterwave communication are investigated in detail. We examine key security threats such as identity forgery, data interception, and denial-of-service attacks, and assess the AI-enhanced defense measures such as intrusion detection systems and blockchainbased trust models. Applications, like autonomous platooning, and collaborative vehicle authentication provide additional examples of AI technologies’ added value in the context of vehicular communications and safety. The paper concludes by providing open issues and future directions, including quantum-resistant protocols, lightweight AI models and cognitive networking in the context AI-driven 5G-VANET ecosystems.
CA-HBCA: A Software Engineering Framework for Secure, Scalable, and Adaptive Healthcare Blockchain Systems Qasim, Mustafa Moosa; Altmemi, Jalal M. H.; Ali, Akram Hussain Abd; Al-Shareeda‬‏, ‪Mahmood A.; Almaiah, Mohammed Amin; Shehab, Rami
Journal of Robotics and Control (JRC) Vol. 6 No. 4 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i4.26643

Abstract

Secure, scalable, and compliant solutions are becoming a requirement for healthcare systems handling sensitive medical data. Blockchain presents unique opportunities to create transparency and trust that is decentralized, yet has inherent challenges posed by scalability, sustainability and regulation. This study presents CA-HBCA, a Cognitive and Adaptive Software Engineering Framework for intelligent healthcare blockchain applications. The novel contribution of the research is the combination of four sledging modules, such as an AIbased cognitive security layer that triggers real-time anomaly detection, an adaptive sustainability engine that optimises energyperformance, a DevSecOps-based continuous delivery pipline, and a HL7/FHIR-compliant interoperability and consent management layer. Methodologically, the FEACAN was realized with Solidity, TensorFlow, and Ethereum/Hyperledger testnets, and tested by simulating healthcare scenarios such as EHR exchange, and adversary search. We obtained 93.2% precision of anomaly detection, 17.6% reduction of energy consumption, 42 transactions per second throughput in Hyperledger, and 98.7% of success rate of HL7-FHIR transformation, etc. The framework also demonstrated 100% smart contract–based consent compliance under test cases. The results indicate that CA-HBCA can be employed for the establishment of secure, sustainable and regulation-compliant blockchains in digital health infrastructures. In the future, we will also carry out validation with clinical real data sets and investigate the scalability in a variety of healthcare settings.
Co-Authors Abbood, Abdulnasser AbdulJabbar Abdulhamed, Mohamed Abdulrahman Abdulsada, Ali M. AL-Shammri, Faris K. Alaidany, Ali A. AlAli, Rommel Ali, Akram Hussain Abd Almaiah, Mohammed Amin Altmemi, Jalal M. H. Alzamili, Zainab Marid Faleh, May Adnan Qasim, Mustafa Moosa Saare, Murtaja Ali Shehab, Rami