Creating a Secure Autonomous Vehicle System Using a Neuro-Fuzzy System that Merges Artificial Neural Networks and Fuzzy Interface Systems

[1] V. SKRICKIJ, E. ŠABANOVIČ, AND V. ŽURAULIS, “Autonomous road vehicles: recent issues and expectations,” IET Intelligent Transport Systems, vol. 14, no. 6, pp. 471–479, Jun. 2020, doi: 10.1049/IET-ITS.2018.5513. Search in Google Scholar

[2] R. KOMISSAROV AND A. WOOL, “Spoofing Attacks Against Vehicular FMCW Radar,” pp. 91–97, Nov. 2021, doi: 10.1145/3474376.3487283. Search in Google Scholar

[3] M. SADAF ET AL., “Connected and Automated Vehicles: Infrastructure, Applications, Security, Critical Challenges, and Future Aspects,” Technologies 2023, Vol. 11, Page 117, vol. 11, no. 5, p. 117, Sep. 2023, doi: 10.3390/TECHNOLOGIES11050117. Search in Google Scholar

[4] X. WANG, X. LIN, AND M. LI, “Aggregate modeling and equilibrium analysis of the crowdsourcing market for autonomous vehicles,” Transp Res Part C Emerg Technol, vol. 132, p. 103362, Nov. 2021, doi: 10.1016/J.TRC.2021.103362. Search in Google Scholar

[5] R. W. CHALMERS, D. H. SCHELDT, T. M. NEIGHOFF, S. J. WITWICKI, AND R. J. BAMBERGER, “Cooperating unmanned vehicles,” Collection of Technical Papers - AIAA 1st Intelligent Systems Technical Conference, vol. 1, pp. 244–251, 2004, doi: 10.2514/6.2004-6252. Search in Google Scholar

[6] T. DAVENPORT, A. GUHA, D. GREWAL, AND T. BRESSGOTT, “How artificial intelligence will change the future of marketing,” J Acad Mark Sci, vol. 48, no. 1, pp. 24–42, Jan. 2020, doi: 10.1007/S11747-019-00696-0/FIGURES/2. Search in Google Scholar

[7] L. JIA ET AL., “On autonomous transportation systems”, doi: 10.1108/SRT-06-2022-0015. Search in Google Scholar

[8] B. SELMA AND S. CHOURAQUI, “Neuro-fuzzy controller to navigate an unmanned vehicle,” Springerplus, vol. 2, no. 1, pp. 1–8, 2013, doi: 10.1186/2193-1801-2-188. Search in Google Scholar

[9] “(PDF) Autonomous System Controller for Vehicles Using Neuro-Fuzzy.” Accessed: May 10, 2024. [Online]. Available: https://www.researchgate.net/publication/259080180_Autonomous_System_Controller_for_Vehicles_Using_Neuro-Fuzzy Search in Google Scholar

[10] K. ASHA ET AL., “Analysis of Automotive Security Risk using Cyber Security,” 2023 International Conference on Network, Multimedia and Information Technology, NMITCON 2023, 2023, doi: 10.1109/NMITCON58196.2023.10275969. Search in Google Scholar

[11] S. R. SHETTY AND D. H. Manjaiah, “Adaptive Neuro-Fuzzy Technique for Jamming Detection in VANETs,” Lecture Notes in Networks and Systems, vol. 479, pp. 571–580, 2023, doi: 10.1007/978-981-19-3148-2_49. Search in Google Scholar

[12] B. AMAR BENSABER, C. G. PEREIRA DIAZ, AND Y. LAHROUNI, “Design and modeling an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the prediction of a security index in VANET,” J Comput Sci, vol. 47, p. 101234, Nov. 2020, doi: 10.1016/J.JOCS.2020.101234. Search in Google Scholar

[13] R. GUNDU AND M. MALEKI, “Securing CAN Bus in Connected and Autonomous Vehicles Using Supervised Machine Learning Approaches”, doi: 10.1109/eIT53891.2022.9813985. Search in Google Scholar

[14] C. YOUNG, J. ZAMBRENO, H. OLUFOWOBI, AND G. BLOOM, “Survey of automotive controller area network intrusion detection systems,” IEEE Des Test, vol. 36, no. 6, pp. 48–55, Dec. 2019, doi: 10.1109/MDAT.2019.2899062. Search in Google Scholar

[15] X. MO, P. CHEN, J.WANG, AND C. WANG, “Anomaly Detection of Vehicle CAN Network Based on Message Content,” Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 284, pp. 96–104, 2019, doi: 10.1007/978-3-030-21373-2_9. Search in Google Scholar

[16] V. H. LE, J. DEN HARTOG, AND N. ZANNONE, “Security and privacy for innovative automotive applications: A survey,” Comput Commun, vol. 132, pp. 17–41, Nov. 2018, doi: 10.1016/J.COMCOM.2018.09.010. Search in Google Scholar

[17] A. REHMAN JAVED, S. UR REHMAN, M. ULLAH KHAN, M. ALAZAB, S. MEMBER, AND T.G. REDDY, “CANintelliIDS: Detecting In-Vehicle Intrusion Attacks on a Controller Area Network Using CNN and Attention-Based GRU”, doi: 10.1109/TNSE.2021.3059881. Search in Google Scholar

[18] H. ZHANG, X. MENG, X. ZHANG, AND Z. LIU, “CANsec: A Practical in-Vehicle Controller Area Network Security Evaluation Tool”, doi: 10.3390/s20174900. Search in Google Scholar