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Adversarial Robustness Verification and Attack Synthesis in Stochastic Systems. (arXiv:2110.02125v2 [cs.CR] UPDATED)
Aug. 2, 2022, 1:20 a.m. | Lisa Oakley, Alina Oprea, Stavros Tripakis
cs.CR updates on arXiv.org arxiv.org
Probabilistic model checking is a useful technique for specifying and
verifying properties of stochastic systems including randomized protocols and
reinforcement learning models. Existing methods rely on the assumed structure
and probabilities of certain system transitions. These assumptions may be
incorrect, and may even be violated by an adversary who gains control of system
components.
In this paper, we develop a formal framework for adversarial robustness in
systems modeled as discrete time Markov chains (DTMCs). We base our framework
on existing …
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