SMART VEHICLE CYBERSECURITY: IMPLEMENTING AN AUTONOMOUS AND ADAPTIVE INTRUSION RESPONSE SYSTEM
DOI:
https://doi.org/10.11113/aej.v15.24631Keywords:
Autonomous vehicles, Intrusion response system, Cybersecurity, Intelligent vehicles, Linear Programming, AI-based mechanisms.Abstract
As smart vehicles are becoming more common, protecting them from cyberattacks has become very important. To address this issue, this paper introduces an automatic intrusion response system (IRS) designed especially for intelligent vehicles. The system is able to quickly analyze the effect of a cyberattack and choose the best response method in real time, making vehicle operations more secure. The proposed IRS offers several key features. First, it provides a clear analysis of different response methods that can be used during cyber intrusions. Second, it introduces a framework that evaluates both the cost and the impact of each response. Third, it applies decision-making tools such as Simple Additive Weighting (SAW), Linear Programming (LP), game theory, and artificial intelligence–based approaches to select the most effective response strategy. Extensive testing shows that the system performs strongly in terms of response quality, time efficiency, and resource usage. This study proposes a hybrid SAW-LP method that combines rapid multi-criteria ranking with constraint-based optimization. Experimental evaluation shows that the hybrid approach reduced response selection time by 32% and improved decision accuracy by 12% compared to standalone algorithms.
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