  Stealthy attacks on Industrial Control Systems can cause significant damage
while evading detection. In this paper, instead of focusing on the detection of
stealthy attacks, we aim to provide early warnings to operators, in order to
avoid physical damage and preserve in advance data that may serve as an
evidence during an investigation. We propose a framework to provide grounds for
suspicion, i.e. preliminary indicators reflecting the likelihood of success of
a stealthy attack. We propose two grounds for suspicion based on the behaviour
of the physical process: (i) feasibility of a stealthy attack, and (ii)
proximity to unsafe operating regions. We propose a metric to measure grounds
for suspicion in real-time and provide soundness principles to ensure that such
a metric is consistent with the grounds for suspicion. We apply our framework
to Linear Time-Invariant (LTI) systems and formulate the suspicion metric
computation as a real-time reachability problem. We validate our framework on a
case study involving the benchmark Tennessee-Eastman process. We show through
numerical simulation that we can provide early warnings well before a potential
stealthy attack can cause damage, while incurring minimal load on the network.
Finally, we apply our framework on a use case to illustrate its usefulness in
supporting early evidence collection.
