Data-injection attacks in stochastic control systems: Detectability and performance tradeoffs

• Autores: Cheng-Zong Bai-, Fabio Pasqualetti, Vijay Gupta
• Localización: Automatica: A journal of IFAC the International Federation of Automatic Control, ISSN 0005-1098, Vol. 82, 2017, págs. 251-260
• Idioma: inglés
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• Resumen

  • Abstract Consider a stochastic process being controlled across a communication channel. The control signal that is transmitted across the control channel can be replaced by a malicious attacker. The controller is allowed to implement any arbitrary detection algorithm to detect if an attacker is present. This work characterizes some fundamental limitations of when such an attack can be detected, and quantifies the performance degradation that an attacker that seeks to be undetected or stealthy can introduce.