  Cyber-physical systems (CPS) have been increasingly attacked by hackers.
Recent studies have shown that CPS are especially vulnerable to insider
attacks, in which case the attacker has full knowledge of the systems
configuration. To better prevent such types of attacks, we need to understand
how insider attacks are generated. Typically, there are three critical aspects
for a successful insider attack: (i) Maximize damage, (ii) Avoid detection and
(iii) Minimize the attack cost. In this paper we propose a Stealthy Attack
GEneration (SAGE) framework by formulizing a novel optimization problem
considering these three objectives and the physical constraints of the CPS. By
adding small worst-case perturbations to the system, the SAGE attack can
generate significant damage, while remaining undetected by the systems
monitoring algorithms. The proposed methodology is evaluated on several anomaly
detection algorithms. The results show that SAGE attacks can cause severe
damage while staying undetected and keeping the cost of an attack low. Our
method can be accessed in the supplementary material of this paper to aid
researcher and practitioners in the design and development of resilient CPS and
detection algorithms.
