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This paper studies a security problem for a class cloud-connected multi-agent systems, where autonomous agents coordinate via a combination of short-range ad-hoc communication links and long-range cloud services. We consider a simplified model for the dynamics of a cloud-connected multi-agent system and attacks, where the states evolve according to linear time-invariant impulsive dynamics, and attacks are modeled as exogenous inputs designed by an omniscent attacker that alters the continuous and impulsive updates. We propose a definition of attack detectability, characterize the existence of stealthy attacks as a function of the system parameters and attack properties, and design a family of undetectable attacks. We illustrate our results on a cloud-based surveillance example.

In this paper, we study a security problem for attack detection in a class of cyber-physical systems consisting of discrete computerized components interacting with continuous agents. We consider an attacker that may inject recurring signals on both the physical dynamics of the agents and the discrete interactions. We model these attacks as additive unknown inputs with appropriate input signatures and timing characteristics. Using hybrid systems modeling tools, we design a novel hybrid attack monitor and, under reasonable assumptions, show that it is able to detect the considered class of recurrent attacks. Finally, we illustrate the general hybrid attack monitor using a specific finite time convergent observer and show its effectiveness on a simplified model of a cloud-connected network of autonomous vehicles.