Privacy Preservation Techniques in V2X Ecosystems: Safeguarding Individual Privacy in Connected Vehicle Environments
Keywords:
V2X ecosystems, privacy preservation, anonymization techniques, data minimization, user consent mechanisms, connected vehicles, privacy-by-designAbstract
In recent years, the advancement of connected vehicle technologies has revolutionized transportation systems worldwide. The seamless exchange of data between vehicles, infrastructure, and other entities has led to significant improvements in transportation efficiency, safety, and convenience. However, alongside these benefits, concerns have emerged regarding the privacy implications of Vehicle-to-Everything (V2X) ecosystems.
The proliferation of V2X communication systems raises fundamental questions about the protection of individuals' privacy rights. As vehicles become increasingly interconnected, vast amounts of data are exchanged, including sensitive information about drivers, passengers, and their surroundings. The potential for misuse or unauthorized access to this data has sparked discussions about the need for robust privacy preservation techniques within V2X environments.
This article aims to address these concerns by exploring various privacy preservation techniques tailored to V2X ecosystems. Specifically, the article examines methods for anonymizing data, minimizing personal data collection, and ensuring the implementation of robust and transparent user consent mechanisms.
Anonymization techniques play a crucial role in protecting individual privacy within V2X ecosystems. By dissociating personal identifiers from the transmitted data, anonymization methods such as pseudonymization, encryption, and data aggregation aim to prevent the identification of individuals while still allowing for the exchange of valuable information.
Furthermore, minimizing personal data collection is essential for reducing privacy risks in V2X environments. By implementing selective data collection mechanisms and adhering to data minimization principles, stakeholders can limit the collection of unnecessary information and mitigate the potential for privacy breaches.
Ensuring robust and transparent user consent mechanisms is another key aspect of privacy preservation in V2X ecosystems. Empowering users to make informed decisions about the sharing and utilization of their personal data fosters trust and accountability within the system. By incorporating privacy-by-design principles into V2X systems, developers can prioritize privacy considerations from the outset, thereby enhancing user confidence in the protection of their privacy rights.
In conclusion, as connected vehicle technologies continue to evolve, it is imperative to prioritize the preservation of individual privacy within V2X ecosystems. By implementing a combination of anonymization techniques, data minimization strategies, and robust user consent mechanisms, stakeholders can mitigate privacy risks and uphold privacy standards in the increasingly interconnected world of transportation.
References
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.
Pulicharla, Mohan Raja. "Hybrid Quantum-Classical Machine Learning Models: Powering the Future of AI." Journal of Science & Technology 4.1 (2023): 40-65.
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.
Chi, K., Ness, S., Muhammad, T., & Pulicharla, M. R. Addressing Challenges, Exploring Techniques, and Seizing Opportunities for AI in Finance.
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.
Sourbron, Steven, et al. "Pixel-by-pixel deconvolution of bolus-tracking data: optimization and implementation." Physics in Medicine & Biology 52.2 (2006): 429.
Othmane, Lotfi Ben, et al. "A survey of security and privacy in connected vehicles." Wireless sensor and mobile ad-hoc networks: vehicular and space applications (2015): 217-247.
Zavvos, Efstathios, et al. "Privacy and Trust in the Internet of Vehicles." IEEE Transactions on Intelligent Transportation Systems 23.8 (2021): 10126-10141.
Liu, Jun, and Asad J. Khattak. "Delivering improved alerts, warnings, and control assistance using basic safety messages transmitted between connected vehicles." Transportation research part C: emerging technologies 68 (2016): 83-100.
Mujahid, Muhammad Akram Akram, et al. "Emergency messages dissemination challenges through connected vehicles for efficient intelligent transportation systems: a review." Baghdad Science Journal 17.4 (2020): 1304-1304.
Ghazi, Muhammad Uzair, et al. "Emergency message dissemination in vehicular networks: A review." Ieee Access 8 (2020): 38606-38621.
Huang, Qinlong, et al. "Secure and privacy-preserving warning message dissemination in cloud-assisted internet of vehicles." 2019 IEEE Conference on Communications and Network Security (CNS). IEEE, 2019.
Du, Lili, and Hoang Dao. "Information dissemination delay in vehicle-to-vehicle communication networks in a traffic stream." IEEE Transactions on Intelligent Transportation Systems 16.1 (2014): 66-80.
Bodkhe, Umesh, and Sudeep Tanwar. "V2XCom: Lightweight and secure message dissemination scheme for Internet of vehicles." Security and Privacy: e352.
Chen, Jieqiong, et al. "A topological approach to secure message dissemination in vehicular networks." IEEE Transactions on Intelligent Transportation Systems 21.1 (2019): 135-148.Noh, Jaewon, Sangil Jeon, and Sunghyun Cho. "Distributed blockchain-based message authentication scheme for connected vehicles." Electronics 9.1 (2020): 74.
Ullah, Ata, et al. "Emergency message dissemination schemes based on congestion avoidance in VANET and vehicular FoG computing." IEEE Access 7 (2018): 1570-1585.
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.
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