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A Trailblazing Framework of Security Assessment for Traffic Data Management

Abdulaziz Attaallah1, Khalil al-Sulbi2, Areej Alasiry3, Mehrez Marzougui3, Neha Yadav4, Syed Anas Ansar5,*, Pawan Kumar Chaurasia4, Alka Agrawal4

1 Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
2 Department of Computer Science, Al-Qunfudah Computer College, Umm Al-Qura University, Mecca, Saudi Arabia
3 College of Computer Science, King Khalid University, Abha, 61421, Saudi Arabia
4 Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow, 226025, Uttar Pradesh, India
5 Department of Computer Applications, Babu Banarasi Das University, Lucknow, 226028, Uttar Pradesh, India

* Corresponding Author: Syed Anas Ansar. Email: email

Intelligent Automation & Soft Computing 2023, 37(2), 1853-1875. https://doi.org/10.32604/iasc.2023.039761

Abstract

Connected and autonomous vehicles are seeing their dawn at this moment. They provide numerous benefits to vehicle owners, manufacturers, vehicle service providers, insurance companies, etc. These vehicles generate a large amount of data, which makes privacy and security a major challenge to their success. The complicated machine-led mechanics of connected and autonomous vehicles increase the risks of privacy invasion and cyber security violations for their users by making them more susceptible to data exploitation and vulnerable to cyber-attacks than any of their predecessors. This could have a negative impact on how well-liked CAVs are with the general public, give them a poor name at this early stage of their development, put obstacles in the way of their adoption and expanded use, and complicate the economic models for their future operations. On the other hand, congestion is still a bottleneck for traffic management and planning. This research paper presents a blockchain-based framework that protects the privacy of vehicle owners and provides data security by storing vehicular data on the blockchain, which will be used further for congestion detection and mitigation. Numerous devices placed along the road are used to communicate with passing cars and collect their data. The collected data will be compiled periodically to find the average travel time of vehicles and traffic density on a particular road segment. Furthermore, this data will be stored in the memory pool, where other devices will also store their data. After a predetermined amount of time, the memory pool will be mined, and data will be uploaded to the blockchain in the form of blocks that will be used to store traffic statistics. The information is then used in two different ways. First, the blockchain’s final block will provide real-time traffic data, triggering an intelligent traffic signal system to reduce congestion. Secondly, the data stored on the blockchain will provide historical, statistical data that can facilitate the analysis of traffic conditions according to past behavior.

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Cite This Article

APA Style
Attaallah, A., al-Sulbi, K., Alasiry, A., Marzougui, M., Yadav, N. et al. (2023). A trailblazing framework of security assessment for traffic data management. Intelligent Automation & Soft Computing, 37(2), 1853-1875. https://doi.org/10.32604/iasc.2023.039761
Vancouver Style
Attaallah A, al-Sulbi K, Alasiry A, Marzougui M, Yadav N, Ansar SA, et al. A trailblazing framework of security assessment for traffic data management. Intell Automat Soft Comput . 2023;37(2):1853-1875 https://doi.org/10.32604/iasc.2023.039761
IEEE Style
A. Attaallah et al., “A Trailblazing Framework of Security Assessment for Traffic Data Management,” Intell. Automat. Soft Comput. , vol. 37, no. 2, pp. 1853-1875, 2023. https://doi.org/10.32604/iasc.2023.039761



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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