Published 05-03-2024
Keywords
- V2X Communication,
- Security Protocols,
- Encryption,
- Authentication,
- Quantum Key Distribution
- Homomorphic Encryption,
- Elliptic Curve Cryptography,
- Post-Quantum Cryptography,
- Standards,
- Future Directions ...More
How to Cite
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Abstract
Vehicle-to-Everything (V2X) communication represents a pivotal technological advancement with the potential to significantly transform road safety, traffic efficiency, and overall transportation systems. Through V2X, vehicles, infrastructure, pedestrians, and other road users can exchange vital information in real-time, enabling proactive decision-making and enhancing situational awareness on the road. However, the successful realization of these benefits hinges on the assurance of secure data exchange within the V2X ecosystem.
This research article delves into the critical aspect of ensuring the security of data transmitted among vehicles, infrastructure components, and various road participants in V2X communication networks. Recognizing the paramount importance of security in fostering trust and reliability within these interconnected systems, the study focuses on the development and implementation of advanced encryption and authentication protocols meticulously crafted to address the unique demands and challenges inherent in V2X communications.
By meticulously analyzing the multifaceted challenges confronting V2X communication security, encompassing threats, vulnerabilities, performance considerations, and privacy concerns, this research endeavors to provide a comprehensive understanding of the security landscape in V2X ecosystems. Furthermore, the article scrutinizes existing security protocols such as the IEEE 1609.2 Standard, ETSI ITS-G5, and security mechanisms in Cellular V2X (C-V2X), elucidating their strengths, limitations, and areas for improvement.
Moreover, the study explores cutting-edge encryption techniques, including Quantum Key Distribution (QKD), Homomorphic Encryption, Elliptic Curve Cryptography (ECC), and Post-Quantum Cryptography (PQC), evaluating their suitability and efficacy in fortifying the security posture of V2X communication networks. Similarly, authentication mechanisms such as certificate-based authentication, identity-based authentication, and group signature schemes are examined in depth to ascertain their applicability and effectiveness in V2X contexts.
Through an integrative approach, this research endeavors to facilitate the seamless assimilation of advanced security protocols into V2X systems, acknowledging and addressing implementation challenges, interoperability considerations, scalability imperatives, and real-world deployment complexities. Furthermore, the article presents case studies and experimental results derived from simulation studies, field trials, and testbed experiments, providing empirical insights into the performance and feasibility of proposed security frameworks.
Looking ahead, the research delineates future directions and emerging technologies poised to shape the evolution of V2X communication security, encompassing standardization efforts, machine learning for anomaly detection, blockchain integration, and the convergence with autonomous vehicle technologies. By synthesizing the findings, recommendations, and implications articulated herein, this research aims to contribute substantively to the establishment of robust security frameworks underpinning the seamless and secure operation of V2X communication networks, thereby fostering trust, reliability, and resilience in future transportation ecosystems.
References
- Chen, Shanzhi, et al. "Vehicle-to-everything (V2X) services supported by LTE-based systems and 5G." IEEE Communications Standards Magazine 1.2 (2017): 70-76.
- MacHardy, Zachary, et al. "V2X access technologies: Regulation, research, and remaining challenges." IEEE Communications Surveys & Tutorials 20.3 (2018): 1858-1877.
- Abboud, Khadige, Hassan Aboubakr Omar, and Weihua Zhuang. "Interworking of DSRC and cellular network technologies for V2X communications: A survey." IEEE transactions on vehicular technology 65.12 (2016): 9457-9470.
- Pulicharla, M. R. (2023). A Study On a Machine Learning Based Classification Approach in Identifying Heart Disease Within E-Healthcare. J Cardiol & Cardiovasc Ther, 19(1), 556004.
- Molina-Masegosa, Rafael, and Javier Gozalvez. "LTE-V for sidelink 5G V2X vehicular communications: A new 5G technology for short-range vehicle-to-everything communications." IEEE Vehicular Technology Magazine 12.4 (2017): 30-39.
- Chen, Shanzhi, et al. "LTE-V: A TD-LTE-based V2X solution for future vehicular network." IEEE Internet of Things journal 3.6 (2016): 997-1005.
- Abbas, Fakhar, Pingzhi Fan, and Zahid Khan. "A novel low-latency V2V resource allocation scheme based on cellular V2X communications." IEEE Transactions on Intelligent Transportation Systems 20.6 (2018): 2185-2197.
- Gonzalez-Martín, Manuel, et al. "Analytical models of the performance of C-V2X mode 4 vehicular communications." IEEE Transactions on Vehicular Technology 68.2 (2018): 1155-1166.
- Hobert, Laurens, et al. "Enhancements of V2X communication in support of cooperative autonomous driving." IEEE communications magazine 53.12 (2015): 64-70.
- Vukadinovic, Vladimir, et al. "3GPP C-V2X and IEEE 802.11 p for Vehicle-to-Vehicle communications in highway platooning scenarios." Ad Hoc Networks 74 (2018): 17-29.
- Muhammad, Mujahid, and Ghazanfar Ali Safdar. "Survey on existing authentication issues for cellular-assisted V2X communication." Vehicular Communications 12 (2018): 50-65.
- Toghi, Behrad, et al. "Multiple access in cellular V2X: Performance analysis in highly congested vehicular networks." 2018 IEEE Vehicular Networking Conference (VNC). IEEE, 2018.
- Lee, Kwonjong, et al. "Latency of cellular-based V2X: Perspectives on TTI-proportional latency and TTI-independent latency." Ieee Access 5 (2017): 15800-15809.
- Pfitzmann, Andreas, and Marit Hansen. "A terminology for talking about privacy by data minimization: Anonymity, unlinkability, undetectability, unobservability, pseudonymity, and identity management." (2010).
- Ghosal, Amrita, and Mauro Conti. "Security issues and challenges in V2X: A survey." Computer Networks 169 (2020): 107093.
- Lu, Ning, et al. "Connected vehicles: Solutions and challenges." IEEE internet of things journal 1.4 (2014): 289-299.
- Huang, Cheng. "Effective Privacy-Preserving Mechanisms for Vehicle-to-Everything Services." (2020).
- Facchinei, Francisco, Gesualdo Scutari, and Simone Sagratella. "Parallel selective algorithms for nonconvex big data optimization." IEEE Transactions on Signal Processing 63.7 (2015): 1874-1889.
- Richtárik, Peter, and Martin Takáč. "Parallel coordinate descent methods for big data optimization." Mathematical Programming 156 (2016): 433-484.
- Shrestha, Rakesh, et al. "Evolution of V2X communication and integration of blockchain for security enhancements." Electronics 9.9 (2020): 1338.
- Abdelkader, Ghadeer, Khalid Elgazzar, and Alaa Khamis. "Connected vehicles: Technology review, state of the art, challenges and opportunities." Sensors 21.22 (2021): 7712.
- Zoghlami, Chaima, Rahim Kacimi, and Riadh Dhaou. "5G-enabled V2X communications for vulnerable road users safety applications: a review." Wireless Networks 29.3 (2023): 1237-1267.
- Glancy, Dorothy J. "Autonomous and automated and connected cars-oh my! First generation autonomous cars in the legal ecosystem." Minn. JL Sci. & Tech. 16 (2015): 619.
- Aldhanhani, Tasneim, et al. "Future Trends in Smart Green IoV: Vehicle-to-Everything in the Era of Electric Vehicles." IEEE Open Journal of Vehicular Technology (2024).
- Storck, Carlos Renato, and Fátima Duarte-Figueiredo. "A 5G V2X ecosystem providing internet of vehicles." Sensors 19.3 (2019): 550.
- Zhou, Haibo, et al. "Evolutionary V2X technologies toward the Internet of vehicles: Challenges and opportunities." Proceedings of the IEEE 108.2 (2020): 308-323.
- Bréhon–Grataloup, Lucas, Rahim Kacimi, and André-Luc Beylot. "Mobile edge computing for V2X architectures and applications: A survey." Computer Networks 206 (2022): 108797.
- Patrik Viktor, Monika Fodor, "Examining Internet of Things (IoT) Devices: A Comprehensive Analysis", 2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI), pp.000115-000120, 2024.
- Rehman, Abdul & Valentini, Roberto & Cinque, Elena & Di Marco, Piergiuseppe & Santucci, Fortunato. (2023). On the Impact of Multiple Access Interference in LTE-V2X and NR-V2X Sidelink Communications. Sensors. 23. 4901. 10.3390/s23104901.
- He, YouLin & Huang, Xu & Hu, ZhiHang & Tao, XingYuan & Su, Che & Yu, YuChengQing. (2023). Handover mechanisms in VMC systems: Evaluating the reliability of V2X as an alternative to fiber networks in handover areas. Theoretical and Natural Science. 28. 174-187. 10.54254/2753-8818/28/20230470.
- Aledhari, Mohammed, et al. "A deep learning-based data minimization algorithm for fast and secure transfer of big genomic datasets." IEEE transactions on big data 7.2 (2018): 271-284.
- Yi, Jiao-Hong, et al. "An improved NSGA-III algorithm with adaptive mutation operator for Big Data optimization problems." Future Generation Computer Systems 88 (2018): 571-585.
- Lerner, Alberto, and Dennis Shasha. "AQuery: Query language for ordered data, optimization techniques, and experiments." Proceedings 2003 VLDB Conference. Morgan Kaufmann, 2003.
- Pargaonkar, Shravan. "A Review of Software Quality Models: A Comprehensive Analysis." Journal of Science & Technology 1.1 (2020): 40-53.
- Nalluri, Mounika, et al. "MACHINE LEARNING AND IMMERSIVE TECHNOLOGIES FOR USER-CENTERED DIGITAL HEALTHCARE INNOVATION." Pakistan Heart Journal 57.1 (2024): 61-68.
- Palle, Ranadeep Reddy. "Evolutionary Optimization Techniques in AI: Investigating Evolutionary Optimization Techniques and Their Application in Solving Optimization Problems in AI." Journal of Artificial Intelligence Research 3.1 (2023): 1-13.
- Ding, Liang, et al. "Understanding and improving lexical choice in non-autoregressive translation." arXiv preprint arXiv:2012.14583 (2020).
- Ding, Liang, Di Wu, and Dacheng Tao. "Improving neural machine translation by bidirectional training." arXiv preprint arXiv:2109.07780 (2021).
- Nalluri, Mounika, et al. "AUTONOMOUS HEALTH MONITORING AND ASSISTANCE SYSTEMS USING IOT." Pakistan Heart Journal 57.1 (2024): 52-60.
- Pargaonkar, Shravan. "Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering." Journal of Science & Technology 1.1 (2020): 61-66.
- Nalluri, Mounika, et al. "INTEGRATION OF AI, ML, AND IOT IN HEALTHCARE DATA FUSION: INTEGRATING DATA FROM VARIOUS SOURCES, INCLUDING IOT DEVICES AND ELECTRONIC HEALTH RECORDS, PROVIDES A MORE COMPREHENSIVE VIEW OF PATIENT HEALTH." Pakistan Heart Journal 57.1 (2024): 34-42.
- Ding, Liang, Longyue Wang, and Dacheng Tao. "Self-attention with cross-lingual position representation." arXiv preprint arXiv:2004.13310 (2020).
- Pargaonkar, Shravan. "Future Directions and Concluding Remarks Navigating the Horizon of Software Quality Engineering." Journal of Science & Technology 1.1 (2020): 67-81.
- Pargaonkar, Shravan. "Quality and Metrics in Software Quality Engineering." Journal of Science & Technology 2.1 (2021): 62-69.
- Pulimamidi, R., and P. Ravichandran. "Enhancing Healthcare Delivery: AI Applications In Remote Patient Monitoring." Tuijin Jishu/Journal of Propulsion Technology 44.3: 3948-3954.
- Ding, Liang, et al. "Rejuvenating low-frequency words: Making the most of parallel data in non-autoregressive translation." arXiv preprint arXiv:2106.00903 (2021).
- Pargaonkar, Shravan. "The Crucial Role of Inspection in Software Quality Assurance." Journal of Science & Technology 2.1 (2021): 70-77.
- Ding, Liang, et al. "Context-aware cross-attention for non-autoregressive translation." arXiv preprint arXiv:2011.00770 (2020).
- Pargaonkar, Shravan. "Unveiling the Future: Cybernetic Dynamics in Quality Assurance and Testing for Software Development." Journal of Science & Technology 2.1 (2021): 78-84.
- Ding, Liang, et al. "Redistributing low-frequency words: Making the most of monolingual data in non-autoregressive translation." Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2022.
- Pargaonkar, Shravan. "Unveiling the Challenges, A Comprehensive Review of Common Hurdles in Maintaining Software Quality." Journal of Science & Technology 2.1 (2021): 85-94.
- Pargaonkar, S. (2020). A Review of Software Quality Models: A Comprehensive Analysis. Journal of Science & Technology, 1(1), 40-53.
- Pargaonkar, S. (2020). Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering. Journal of Science & Technology, 1(1), 61-66.
- Pargaonkar, S. (2020). Future Directions and Concluding Remarks Navigating the Horizon of Software Quality Engineering. Journal of Science & Technology, 1(1), 67-81.
- Pargaonkar, S. (2021). Quality and Metrics in Software Quality Engineering. Journal of Science & Technology, 2(1), 62-69.
- Pargaonkar, S. (2021). The Crucial Role of Inspection in Software Quality Assurance. Journal of Science & Technology, 2(1), 70-77.
- Pargaonkar, S. (2021). Unveiling the Future: Cybernetic Dynamics in Quality Assurance and Testing for Software Development. Journal of Science & Technology, 2(1), 78-84.
- Pargaonkar, S. (2021). Unveiling the Challenges, A Comprehensive Review of Common Hurdles in Maintaining Software Quality. Journal of Science & Technology, 2(1), 85-94.