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Alternative Title:Securing Intelligent Transportation Systems Against Spoofing Attacks: Spoofing Attack Simulation and Associated Metadata [Dataset title]
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Abstract:Modern transportation networks are increasingly connected and autonomous, thanks to the introduction of real-time sensing and autonomous decision-making capabilities. However, the cyber components enabling connectivity and autonomy are subject to persistent security threats. A major threat is spoofing attacks via injection of falsified information. For transportation networks, a typical form of spoofing attack is to inject non-existent (i.e. ``phantom'') traffic into routing/navigation tools, and real incidents have been reported. Dynamic routing is a classical control strategy applicable to a variety of engineering systems, including transportation, production lines, and communications. In this project, the authors develop novel models and methods to evaluate the reliability/security risk of dynamic routing and to design an efficient deployment of protecting resources. The authors consider a parallel queuing system with a routing mechanism that is subject to faults due to hardware malfunctions or malicious attacks. The proposed approach quantifies the efficiency loss (in terms of queuing delay) due to reliability and/or security failures that occur randomly. The authors study both open-loop and closed-loop (i.e. queuing state-dependent) defending strategies that restrict the reliability/security risk while maintaining an acceptable budget. The authors characterize the structures of the defending strategies and develop algorithms that efficiently compute the strategies. The authors also demonstrate their approach via a series of computational examples.
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