Security of Data Exchange in Automated Traffic Monitoring

11th International Scientific Conference Technics, Informatics and Education – TIE 2026, (pp. 231-237)

АУТОР(И) / AUTHOR(S): Nikola Nikolić , Tanja Sekulić  and Marija Matotek Anđelić

Download Full Pdf   

DOI: https://doi.org/10.46793/TIE26.231N

САЖЕТАК /ABSTRACT:

Traffic as we know it today is extremely complex. There are various command centers from which constant monitoring, control, correction and redirection are carried out in order to improve fluidity and its safety. Modern vehicles are also equipped with various systems that exchange data with control centers, dispatchers, and more and more such systems enable communication between the vehicles themselves, i.e. data exchange. Here, emphasis should be placed on the security of the protocols that exchange data, as well as the security of the data itself. Data manipulation can be carried out in the field of hardware and software. Review of studies dealing with this topic aims to find solutions that have been applied so far that will guarantee constant protection in all segments of the system. That is why more and more such systems and protocols are being developed, as well as dedicated applications with the aim of increasing security. Especially now, when artificial intelligence has become significantly usable and widely used. By searching for studies on Google Scholar, the authors identified studies that addressed the problems of data transmission and processing in automated traffic monitoring and intelligent transport systems. Studies that address traffic automation in smart cities were also considered. The criterion for searching for studies is data security in automated transport systems and traffic monitoring. By searching the databases: Science Direct, IEEE Hplore and Web of Science , in the period from 2010 to 2026, using keywords related to the security of data exchange in automated traffic monitoring, the authors selected 34 studies that address this problem in a modern way. Of these, some studies were used to define the problem (4/34), studies that had the topic of understanding the problem (6/34), most studies relate to data exchange protection techniques (17/34) as well as the development of defensive techniques in the future (7/34), i.e. simulation and training.

КЉУЧНЕ РЕЧИ / KEYWORDS: 

security; data exchange; traffic; intelligent transport systems

 ПРОЈЕКАТ / ACKNOWLEDGEMENT:

ЛИТЕРАТУРА / REFERENCES:

  • Cardona-Alvarez, Y. N., Alvarez-Meza, A. M. and Castellanos-Dominguez, G. (2025). Revolutionizing data exchange through intelligent automation: Insights and trends. Computers, 14(5), 194. https://doi.org/10.3390/computers14050194 http://www.mdpi.com/2073-431X/14/5/194
  • Ameen, H. A., et al. (2019). A deep review and analysis of data exchange in vehicle-to-vehicle communications systems: Coherent taxonomy, challenges, motivations, recommendations, substantial analysis and future directions. IEEE Access, 7, 158349–158378. https://doi.org/10.1109/ACCESS.2019.2949130
  • Alam, T. (2024). Data Privacy and Security in Autonomously Connected Vehicles in a Smart City Environment. Big Data and Cognitive Computing, 8(9), 95. https://doi.org/10.3390/bdcc8090095 http://www.mdpi.com/2504-2289/8/9/95
  • Byabazair, J., O’Hare, G., and Delaney, D. (2020). Data quality and trust: A review of challenges and opportunities for data sharing in the Internet of Things. Electronics, 9(12), 2083. https://doi.org/10.3390/electronics9122083
  • Shakir, A. T., et al. (2024). A systematic review of roadside unit data sharing in ad hoc vehicle networks: a coherent taxonomy, salient features, datasets, metrics, performance measures, motivation, opportunities, challenges and methodological aspects. Discov Appl Sci, 6, 487. http://doi.org/10.1007/с42452-024-06174-9
  • Aoki, S., Yonezawa, T., Kawaguchi, N., Stinkiste, P., & Rajkumar, R. R. (2022). Time-sensitive cooperative perception for real-time data sharing via vehicle communication: Overview, challenges, and future directions. IEEE Internet of Things Magazine, 5(2), 108–113.
  • Das, D., Banerjee, S., Chatterjee, P., Ghosh, U., & Biswas, U. (2023). Blockchain for intelligent transportation systems: Applications, challenges, and opportunities. IEEE Internet of Things Journal, 10(21), 18961–18970.
  • Ali, E. S., Hassan, M. K., Hassan, R., Syed, R. A., Hassan, M. B., Islam, S., Nafi, N. S., & Bevinakopa, S. (2021). Machine learning technologies for secure vehicle-to-vehicle communication in the Internet of Vehicles: Recent progress and applications. Security and Communication Networks, Article 8868355. https://doi.org/10.1155/2021/8868355
  • Rana, K., & Khatri, N. (2024). Automotive intelligence: Unleashing the potential of artificial intelligence beyond advanced driver assistance systems, a comprehensive review. Computers and Electrical Engineering, 117, Article 109237. https://doi.org/10.1016/j.compeleceng.2024.109237
  • Sadaf, M., Iqbal, Z., Javed, A. R., Saba, I., Krichen, M., Majid, S. and Raza, A. (2023). Connected and Automated Vehicles: Infrastructure, Applications, Security, Critical Challenges and Future Aspects. Technologies, 11(5), 117. https://doi.org/10.3390/technologies11050117
  • Khan, R., Mehmood, A., Maple, K., Kuran, K., & Song, H. H. (2024). Performance analysis of blockchain-enabled security and privacy algorithms in connected and autonomous vehicles: A comprehensive review. IEEE Transactions on Intelligent Transportation Systems, 25(6), 4773–4784. https://doi.org/10.1109/TITS.2023.3338521
  • Rabi, M. K., Islam, M. M., & Emon, S. M. (2019). A review of Internet of Things applications in smart traffic management system. 5th International Conference on Advances in Electrical Engineering (ICAEE), 280–285. https://doi.org/10.1109/ICAEE45823.2019.8978330
  • Tripathi, G., Ahad, M. A., & Satyanarayana, M. (2019). The role of blockchain in the Internet of Vehicles (IoV): Issues, challenges, and opportunities. International Conference on Contemporary Computing and Informatics (IC3I), 26–31. https://doi.org/10.1109/IC3I46372.2019.9163013
  • Jayaprakash, M., Elavarasi, T. L. S., & Agoramurthy, M. S. N. (2025). Blockchain-based privacy-preserving protocols for secure data sharing in the Internet of Things: An implementation review. 5th International Conference on Ubiquitous Computing and Social Networks (ICPCSN), 285–290. https://doi.org/10.1109/ICPCSN65215.2025.10931234
  • Gao, C., Wang, G., Shi, W., Wang, Z., & Chen, J. (2022). Autonomous driving safety: State of the art and challenges. IEEE Internet of Things Journal, 9(10), 7572–7595. https://doi.org/10.1109/JIOT.2021.3138684
  • Feng, J. (2023). Analysis of network information security technologies in digital intelligent security strategy. International Conference on Computer Simulation and Modeling, Information Security (CSMIS 2023), 465–470. https://doi.org/10.1109/CSMIS59942.2023.00092
  • Nebione, G. and Calzarosa, M. C. (2020). Application Layer Protocol Security in the Internet of Things: Challenges and Findings. Future Internet, 12(3), 55. http://doi.org/10.3390/fi12030055
  • Almutairi, M. and Sheldon, F. T. (2025). Internet of Things Security and Cloud Integration: A Review of Challenges, Solutions, and Directions. Electronics, 14(7), 1394. https://doi.org/10.3390/electronics14071394
  • Mistry, I., Tanwar, S., Tyagi, S., & Kumar, N. (2020). Blockchain for 5G IoT for industrial automation: A systematic review, solutions and challenges. Mechanical Systems and Signal Processing, 135, Article 106382. https://doi.org/10.1016/j.ymssp.2019.106382
  • Taherdast, H. (2023). Security and the Internet of Things: Benefits, Challenges, and Future Perspectives. Electronics, 12(8), 1901. https://doi.org/10.3390/electronics12081901
  • Khan, H. A., Khan, H., Ghafoor, S., & Khan, M. A. (2025). A study on the security of the Automatic Dependent Surveillance-Broadcast (ADS-B) protocol: Challenges, potential solutions, and future directions. IEEE Communications Surveys & Tutorials, 27(5), 3199–3226. https://doi.org/10.1109/COMST.2024.3491234
  • Durlik, I., Miller, T., Kostecka, E., Zwierzewicz, Z., & Łobodzinska, A. (2024). Cybersecurity in autonomous vehicles — are we ready for the challenge? Electronics, 13(13), 2654. https://doi.org/10.3390/electronics13132654
  • Admass, W. S., Munaye, Y. Y., & Diro, A. A. (2024). Cyber security: State of the art, challenges and future directions. Cyber Security and Applications, 2, Article 100031. https://doi.org/10.1016/j.csa.2023.100031
  • Al-Quayed, F., Tariq, N., Humayun, M., Aslam Khan, F., Atiq Khan, M. and Alnusairi, T. S. (2025). Securing the Road Ahead: An Investigation into Internet of Vehicles Security Based on a Conceptual Blockchain-Based Intrusion Detection System for Smart Cities. Trans Emerging Tel Tech, 36: e70133. http://doi.org/10.1002/ett.70133
  • Alhabib, R., Yadav, P. (2025). Authorization and data validation in autonomous vehicles: a critical review. Discov Appl Sci, 7, 735. http://doi.org/10.1007/с42452-025-07333-2
  • Li, Y., & Liu, Q. (2021). A comprehensive review study on cyberattacks and cybersecurity: New trends and recent developments. Energy Reports, 7, 8176–8186. https://doi.org/10.1016/j.egyr.2021.08.126
  • AlShboul, R., Thabtah, F., Abdelhamid, N., & Al-Diabat, M. (2018). A visualization cybersecurity method based on features’ dissimilarity. Computers & Security, 77, 289–303. https://doi.org/10.1016/j.cose.2018.04.007
  • Kemerer, C. F. (2003). Cybersecurity. Proceedings of the 25th International Conference on Software Engineering, 705–715. https://doi.org/10.1109/ICSE.2003.1201257
  • Jiang, J., Jeusfeld, M. A., Ding, J. & Sandahl, E. (2023). Model-based cybersecurity analysis. Business & Information Systems Engineering, 65(6), 643–676. https://doi.org/10.1007/s12599-023-00811-0
  • Buhler, N., La Fleur, K.G., Hoffman, B., Rajivan, P., Marusic, L., & Leitner, L. (2018).Cyber teaming and role specialization in cybersecurity and defense competition. Psychol, 9:2133. https://doi:10.3389/fpsyg.2018.02133
  • Balon, T., Bagili, I. A. (2023). Cyber competitions: A review of competitions, tools, and systems to support cybersecurity education. Educ Inf Technol, 28, 11759–11791. http://doi.org/10.1007/с10639-022-11451-4
  • Usman, M., Jan, M. A., He, X., & Chen, J. (2019). Exploring the efforts of representation learning in the cybersecurity domain. ACM Computing Surveys, 52(6), Article 111. https://doi.org/10.1145/3364205
  • Shah, A., Ganesan, R., Jajodia, S., Kam, H., & Hutchinson, S. (2023). A novel team formation framework based on performance in a cybersecurity operations center. IEEE Transactions on Services Computing, 16(4), 2359–2371. https://doi.org/10.1109/TSC.2023.3242203
  • Shaukat, K., Luo, S., Varadharajan, V., Hamid, I. A., Chen, S., Liu, D., & Li, J. (2020). Performance comparison and current challenges of using machine learning techniques in cybersecurity. Energies, 13(10), 2509. https://doi.org/10.3390/en13102509

 

Post Views: 19