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CIA Security for Internet of Vehicles and Blockchain-AI Integration

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Abstract

The lack of data security and the hazardous nature of the Internet of Vehicles (IoV), in the absence of networking settings, have prevented the openness and self-organization of the vehicle networks of IoV cars. The lapses originating in the areas of Confidentiality, Integrity, and Authenticity (CIA) have also increased the possibility of malicious attacks. To overcome these challenges, this paper proposes an updated Games-based CIA security mechanism to secure IoVs using Blockchain and Artificial Intelligence (AI) technology. The proposed framework consists of a trustworthy authorization solution three layers, including the authentication of vehicles using Physical Unclonable Functions (PUFs), a flexible Proof-of-Work (dPOW) consensus framework, and AI-enhanced duel gaming. The credibility of the framework is validated by different security analyses, showcasing its superiority over existing systems in terms of security, functionality, computation, and transaction overhead. Additionally, the proposed solution effectively handles challenges like side channel and physical cloning attacks, which many existing frameworks fail to address. The implementation of this mechanism involves the use of a reduced encumbered blockchain, coupled with AI-based authentication through duel gaming, showcasing its efficiency and physical-level support, a feature not present in most existing blockchain-based IoV verification frameworks.

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References

  1. Mezair, T., Djenouri, Y., Belhadi, A., Srivastava, G., Lin, J.C.-W.: Towards an advanced deep learning for the internet of behaviors: Application to connected vehicles. ACM Transactions on Sensor Networks 19(2), 1–18 (2022)

    Article  Google Scholar 

  2. Liang, W., Long, J., Weng, T.-H., Chen, X., Li, K.-C., Zomaya, A.Y.: Tbrs: A trust based recommendation scheme for vehicular cps network. Futur. Gener. Comput. Syst. 92, 383–398 (2019)

    Article  Google Scholar 

  3. Djenouri, Y., Belhadi, A., Djenouri, D., Srivastava, G., Lin, J. C.-W.: A secure intelligent system for internet of vehicles: Case study on traffic forecasting. IEEE Transactions on Intelligent Transportation Systems

  4. Alouache, L., Nguyen, N., Aliouat, M., Chelouah, R.: Survey on iov routing protocols: Security and network architecture. Int. J. Commun Syst 32(2), e3849 (2019)

    Article  Google Scholar 

  5. Liang, H., Wu, J., Mumtaz, S., Li, J., Lin, X., Wen, M.: Mbid: Micro blockchain-based geographical dynamic intrusion detection for v2x. IEEE Commun. Mag. 57(10), 77–83 (2019)

    Article  Google Scholar 

  6. Wu, W., Yang, Z., Li, K.: Internet of vehicles and applications. In: Internet of Things, Elsevier, pp. 299–317 (2016)

  7. Yazdinejad, A., Rabieinejad, E., Hasani, T., Srivastava, G.: A bert-based recommender system for secure blockchain-based cyber physical drug supply chain management. Cluster Computing 1–15 (2023)

  8. Li, X., Ma, J., Wang, W., Xiong, Y., Zhang, J.: A novel smart card and dynamic id based remote user authentication scheme for multi-server environments. Math. Comput. Model. 58(1–2), 85–95 (2013)

    Article  Google Scholar 

  9. Gupta, M., Sharma, B., Tripathi, A., Singh, S., Bhola, A., Singh, R., Dwivedi, A.D.: n-player stochastic duel game model with applied deep learning and its modern implications. Sensors 22(6), 2422 (2022)

    Article  Google Scholar 

  10. Sheikh, M.S., Liang, J., Wang, W.: Security and privacy in vehicular ad hoc network and vehicle cloud computing: a survey. Wireless Communications and Mobile Computing (2020)

  11. Li, X., Xiong, Y., Ma, J., Wang, W.: An efficient and security dynamic identity based authentication protocol for multi-server architecture using smart cards. J. Netw. Comput. Appl. 35(2), 763–769 (2012)

    Article  Google Scholar 

  12. Xu, Y., Ren, J., Zhang, Y., Zhang, C., Shen, B., Zhang, Y.: Blockchain empowered arbitrable data auditing scheme for network storage as a service. IEEE Trans. Serv. Comput. 13(2), 289–300 (2019)

    Google Scholar 

  13. Xu, Y., Zhang, C., Zeng, Q., Wang, G., Ren, J., Zhang, Y.: Blockchain enabled accountability mechanism against information leakage in vertical industry services. IEEE Transactions on Network Science and Engineering 8(2), 1202–1213 (2020)

    Article  MathSciNet  Google Scholar 

  14. Xu, Y., Zhang, C., Wang, G., Qin, Z., Zeng, Q.: A blockchain-enabled deduplicatable data auditing mechanism for network storage services. IEEE Trans. Emerg. Top. Comput. 9(3), 1421–1432 (2020)

    Article  Google Scholar 

  15. Xu, Y., Yan, X., Wu, Y., Hu, Y., Liang, W., Zhang, J.: Hierarchical bidi-rectional rnn for safety-enhanced b5g heterogeneous networks. IEEE Transactions on Network Science and Engineering 8(4), 2946–2957 (2021)

    Article  Google Scholar 

  16. Xu, Y., Zeng, Q., Wang, G., Zhang, C., Ren, J., Zhang, Y.: An efficient privacy-enhanced attribute-based access control mechanism. Concurrency and Computation: Practice and Experience 32(5), e55 (2020)

    Article  Google Scholar 

  17. Xu, Y., Liu, Z., Zhang, C., Ren, J., Zhang, Y., Shen, X.: Blockchain-based trustworthy energy dispatching approach for high renewable energy penetrated power systems. IEEE Internet of Things Journal

  18. Mittal, M., Iwendi, C., Khan, S., Rehman Javed, A.: Analysis of security and energy efficiency for shortest route discovery in low-energy adaptive clustering hierarchy protocol using levenberg-marquardt neural network and gated recurrent unit for intrusion detection system. Transactions on Emerging Telecommunications Technologies 32(6), e3997 (2021)

    Article  Google Scholar 

  19. Anajemba, J.H., Yue, T., Iwendi, C., Chatterjee, P., Ngabo, D., Alnumay, W.S.: A secure multiuser privacy technique for wireless iot networks using stochastic privacy optimization. IEEE Internet Things J. 9(4), 2566–2577 (2021). https://doi.org/10.1109/JIOT.2021.3050755

    Article  Google Scholar 

  20. Vasudev, H., Deshpande, V., Das, D., Das, S.K.: A lightweight mutual authentication protocol for v2v communication in internet of vehicles. IEEE Trans. Veh. Technol. 69(6), 6709–6717 (2020)

    Article  Google Scholar 

  21. Hai, T., Wang, D., Seetharaman, T., Amelesh, M., Sreejith, P., Sharma, V., Ibeke, E., Liu, H.: A novel & innovative blockchain-empowered federated learning approach for secure data sharing in smart city applications. In: International Conference on Advances in Communication Technology and Computer Engineering. Springer, pp. 105–118 (2023)

  22. Bayat, M., Pournaghi, M., Rahimi, M., Barmshoory, M.: Nera: A new and efficient rsu based authentication scheme for vanets. Wireless Netw. 26(5), 3083–3098 (2020)

    Article  Google Scholar 

  23. Polak, B.: ECON 159–Lecture 16–Backward Induction: Reputation and Duels–Open Yale Courses. https://oyc.yale.edu/economics/econ-159/lecture-1

  24. Rathor, S.: A. Agrawal, A robust verification system for recruitment process by using blockchain technology. International Journal of Blockchains and Cryptocurrencies 1(4), 389–399 (2020)

  25. Bajaj, K., Sharma, B., Singh, R.: Integration of wsn with iot applications: a vision, architecture, and future challenges. In: Integration of WSN and IoT for Smart Cities. Springer, pp. 79–102 (2020)

  26. Anajemba, J.H., Tang, Y., Iwendi, C., Ohwoekevwo, A., Srivastava, G., Jo, O.: Realizing efficient security and privacy in iot networks. Sensors 20(9), 2609 (2020)

    Article  Google Scholar 

  27. Anajemba, J.H., Tang, Y., Ansere, J.A., Iwendi, C.: Performance analysis of d2d energy efficient iot networks with relay-assisted underlaying technique. In: IECON 2018-44th Annual Conference of the IEEE Industrial Electronics Society. IEEE, pp. 3864–3869 (2018). https://doi.org/10.1109/IECON.2018.8591373

  28. Mittal, M., Saraswat, L.K., Iwendi, C., Anajemba, J.H.: A neuro-fuzzy approach for intrusion detection in energy efficient 4th International conference on internet of things: Smart innovation and usages (IoT-SIU). IEEE, pp. 1–5 (2019). https://doi.org/10.1109/IoT-SIU.2019.8777501

  29. Siddiqi, M.A., Iwendi, C., Jaroslava, K., Anumbe, N.: Analysis on security related concerns of unmanned aerial vehicle: attacks, limitations, and recommendations. Math. Biosci. Eng. 19(3), 2641–2670 (2022). https://doi.org/10.3934/mbe.2022121

    Article  Google Scholar 

  30. Wang, W., Chen, Q., Yin, Z., Srivastava, G., Gadekallu, T.R., Alsolami, F., Su, C.: Blockchain and puf-based lightweight authentication protocol for wireless medical sensor networks. IEEE Internet Things J. 9(11), 8883–8891 (2021)

    Article  Google Scholar 

  31. Mantey, E.A., Zhou, C., Mani, V., Arthur, J.K., Ibeke, E.: Maintaining privacy for a recommender system diagnosis using blockchain and deep learning. Human-centric computing and information sciences 13 (47) (2023). https://doi.org/10.22967/HCIS.2023.13.047

  32. Yazdinejad, A., Parizi, R.M.: A. Dehghantanha, K.-K. R. Choo, P4-to-blockchain: A secure blockchain-enabled packet parser for software defined networking, Computers & Security 88, 101629 (2020)

  33. Cao, K., Wang, B., Ding, H., Lv, L., Tian, J., Hu, H., Gong, F.: Achieving reliable and secure communications in wireless-powered noma systems. IEEE Trans. Veh. Technol. 70(2), 1978–1983 (2021). https://doi.org/10.1109/TVT.2021.3053093

    Article  Google Scholar 

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Acknowledgements

We would like to thank anonymous re-viewers for their useful suggestions.

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Conceptualization by Celestine Iwendi and Tai Hai; Methodology by Muammer Aksoy; Software by Muammer Aksoy and Senthilkumar Mohan; formal analysis by Tai Hai and Senthilkumar Mohan; Investigation by Ebuka Ibeke and Celestine Iwendi; Resources and data collection by Tai Hai, Senthilkumar Mohan; Writing by: Tai Hai, Muammer Aksoy and Ebuka Ibeke; Validation by: Ebuka Ibeke, Senthilkumar Mohan and Celestine Iwendi. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Celestine Iwendi.

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Hai, T., Aksoy, M., Iwendi, C. et al. CIA Security for Internet of Vehicles and Blockchain-AI Integration. J Grid Computing 22, 43 (2024). https://doi.org/10.1007/s10723-024-09757-3

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