Blockchain-Enhanced Vehicular Ad-hoc Networks (B-VANETs): Decentralized Traffic Coordination and Anonymized Communication
Keywords:
B-VANET, Blockchain, Autonomous Vehicles, Smart Transportation, Traffic CoordinationAbstract
The research systematically evaluates an intelligent transportation system, specifically focusing on Blockchain-based Vehicular Ad Hoc Networks (B-VANETs) through simulations encompassing decentralized traffic coordination, anonymized communication, and data encryption. Employing a detailed methodology, including blockchain simulations and trust score monitoring, the simulations unveil diverse vehicle behaviors in traffic scenarios, highlighting the need to balance acceleration and deceleration. Communication dynamics among autonomous vehicles in B-VANETs vary, emphasizing the importance of optimizing communication strategies. Trust scores evolve dynamically, illustrating the complex nature of trust management within autonomous systems operating in B-VANETs. Six simulations with thoughtfully chosen parameters provide robust data while maintaining computational efficiency. Comparative analysis reveals stable trust scores and traffic coordination, with an average trust score of approximately 1.411, and the system demonstrates computational efficiency, with runtime variations between 1.363 and 1.540 seconds.
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S D, V. S., & C J, P. (2023). A Study on Vision Based Lane Detection Methods for Advanced Driver Assistance Systems. International Journal of Computer Engineering in Research Trends, 10(8), 1–10.
M, P., & K, D. S. D. (2023). ICN Scheme and Proxy re-encryption for Privacy Data Sharing on the Block Chain. International Journal of Computer Engineering in Research Trends, 10(4), 172–176.
S. K. Dwivedi, R. Amin, A. K. Das, M. T. Leung, K.-K. R. Choo, and S. Vollala, “Blockchain-based vehicular ad-hoc networks: A comprehensive survey,” Ad Hoc Netw., vol. 137, no. 102980, p. 102980, 2022.
R. Shrestha, R. Bajracharya, A. P. Shrestha, and S. Y. Nam, “A new type of blockchain for secure message exchange in VANET,” Digit. Commun. Netw., vol. 6, no. 2, pp. 177–186, 2020.
M. Saad, M. K. Khan, and M. B. Ahmad, “Blockchain-enabled vehicular ad hoc networks: A systematic literature review,” Sustainability, vol. 14, no. 7, p. 3919, 2022.
M. Arif, W. Balzano, A. Fontanella, S. Stranieri, G. Wang, and X. Xing, “Integration of 5G, VANETs and Blockchain Technology,” in 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2020, pp. 2007–2013.
M Bhavsingh, B.Pannalal, & K Samunnisa. (2022). Review: Pedestrian Behavior Analysis and Trajectory Prediction with Deep Learning. International Journal of Computer Engineering in Research Trends, 9(12), 263–268.
Ravikumar, G. ., Begum, Z. ., Kumar, A. S. ., Kiranmai, V., Bhavsingh, M., & Kumar, O. K. . (2022). Cloud Host Selection using Iterative Particle-Swarm Optimization for Dynamic Container Consolidation. International Journal on Recent and Innovation Trends in Computing and Communication, 10(1s), 247–253. https://doi.org/10.17762/ijritcc.v10i1s.5846.
Peng, C. Wu, L. Gao, J. Zhang, K.-L. Alvin Yau, and Y. Ji, “Blockchain for vehicular Internet of Things: Recent advances and open issues,” Sensors (Basel), vol. 20, no. 18, p. 5079, 2020.
K. Kaltakis, P. Polyzi, G. Drosatos, and K. Rantos, “Privacy-preserving solutions in blockchain-enabled Internet of vehicles,” Appl. Sci. (Basel), vol. 11, no. 21, p. 9792, 2021.
M. R. Arun, Prof. M. R. Sheeba, & Prof. F. Shabina Fred Rishma. (2020). Comparing BlockChain with other Cryptographic Technologies (DAG, Hashgraph, Holochain). International Journal of Computer Engineering in Research Trends, 7(4), 13–19.
N. Parikh and M. L. Das, “Privacy-preserving services in VANET with misbehavior detection,” in 2017 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), 2017, pp. 1–6.
S. K. A. Theodore, K. R. Gandhi, and V. Palanisamy, “A novel lightweight authentication and privacy-preserving protocol for vehicular ad hoc networks,” Complex Intell. Syst., vol. 9, no. 3, pp. 2981–2991, 2023.
W. Ahmed, W. Di, and D. Mukathe, “Privacy preserving blockchain‐based authentication and trust management in VANETs,” IET Netw., vol. 11, no. 3–4, pp. 89–111, 2022.
Teixeira, J. Ferreira, and J. Macedo, “Systematic literature review of AI/ML techniques applied to VANET routing,” in Lecture Notes in Networks and Systems, Cham: Springer International Publishing, 2022, pp. 339–361.
Ayushi Singh, Gulafsha Shujaat, Isha Singh, Abhishek Tripathi, & Divya Thakur. (2019). A Survey of Blockchain Technology Security. International Journal of Computer Engineering in Research Trends, 6(4), 299–303.
Z. Li, D. Kong, Y. Niu, H. Peng, X. Li, and W. Li, “An overview of AI and blockchain integration for privacy-preserving,” arXiv [cs.CR], 2023.
M. H. Miraz and M. Ali, “Integration of Blockchain and IoT: An enhanced security perspective,” arXiv [cs.CR], 2020.
Namakshenas, “Web3.0 security: Privacy enhancing and anonym auditing in blockchain-based structures,” arXiv [cs.CR], 2023.
M. Al Asqah and T. Moulahi, “Federated learning and Blockchain integration for privacy protection in the Internet of Things: Challenges and solutions,” Future Internet, vol. 15, no. 6, p. 203, 2023.
S. D. Okegbile, J. Cai, and A. S. Alfa, “Performance analysis of blockchain-enabled data-sharing scheme in cloud-edge computing-based IoT networks,” IEEE Internet Things J., vol. 9, no. 21, pp. 21520–21536, 2022.
Waheeb , M. Q. ., SANGEETHA, D., & Raj , R. . (2021). Detection of Various Plant Disease Stages and Its Prevention Method Based on Deep Learning Technique. Research Journal of Computer Systems and Engineering, 2(2), 33:37. Retrieved from https://technicaljournals.org/RJCSE/index.php/journal/article/view/30
D, D. ., Goel, A. K. ., Agrawal, K. K. ., Johri, S. ., & Kumar, A. . (2023). CFLCA: High Performance based Heart disease Prediction System using Fuzzy Learning with Neural Networks. International Journal on Recent and Innovation Trends in Computing and Communication, 11(4), 98–112. https://doi.org/10.17762/ijritcc.v11i4.6392
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