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              <text>Integrating AI and Cybersecurity: Advancing Autonomous Vehicle Security and Response Mechanisms</text>
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              <text>AI integration; Dynamic response mechanisms; Risk mitigation; Vehicle security operation centers</text>
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              <text>The rapid evolution of autonomous and connected vehicles has led to their integration with numerous technologies and software, rendering them vulnerable targets for cybersecurity attacks. While efforts have traditionally focused on preventing these attacks, the escalating risk underscores the importance of also vindicating their wallop. Nevertheless, this procedure is often onerous &amp;amp; facade scalability confronted, particularly due to connectivity issues in automobiles. This research advises a vehicle-based vibrant imposition response scheme, enabling swift responses to a variety of incidents and reducing reliance on external security centers. The classification encompasses an inclusive range of probable retorts, a procedure for evaluating retorts, &amp;amp; innumerable assortment approaches. Implemented on an embedded platform, the solution was evaluated using two distinct cyberattack use cases, highlighting its adaptability, responsiveness, volume for dynamic arrangement constraint alterations &amp;amp; nominal memory trail. Concurrently, this paper presents an innovative (AVSF) that synergistically integrates (AI) and cybersecurity techniques to fortify AV resilience against evolving threats. Additionally, the framework incorporates advanced cybersecurity measures such as encryption, authentication, and intrusion detection to mitigate vulnerabilities and safeguard critical AV systems. The fusion of AI and cybersecurity not only enhances AV security posture but also enables intelligent cyber threat monitoring and response capabilities. Extensive simulations and experimental evaluations demonstrate the efficacy of the AVSF in real-time scenarios, contributing to the development of robust security solutions for autonomous vehicle deployment and advancing safer transportation systems in the era of AI-driven mobility.   2024 IEEE.</text>
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              <text>Namburi V.L.; Adapa S.R.; Chamala S.S.K.; Yerram M.; Gupta P.; Upreti K.</text>
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              <text>2024 International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2024 - Proceedings, pp. 253-258.</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>2024-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/ETNCC63262.2024.10767464" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ETNCC63262.2024.10767464&lt;/a&gt;
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              <text>ISBN: 979-835035326-6</text>
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              <text>Namburi V.L., Software Systems Engineer Danlaw Inc, MI, United States; Adapa S.R., Software Engineer OpenLogix LLC, MI, United States; Chamala S.S.K., Software Developer Software Bots Inc, MI, United States; Yerram M., Computer Science with IOT VNRVJIET, Hyderabad, India; Gupta P., Computer Science Engineering ADGIPS, Delhi, India; Upreti K., Dept. of Computer Science, Christ University, Delhi NCR Campus, India</text>
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