Anonymity and uniformity of parameterized probabilistic systems can be verified automatically by synthesizing regular bisimulation relations via automata learning and checking them in the decidable theory of regular structures.
Proving uniformity and independence by self-composition and coupling
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abstract
Proof by coupling is a classical proof technique for establishing probabilistic properties of two probabilistic processes, like stochastic dominance and rapid mixing of Markov chains. More recently, couplings have been investigated as a useful abstraction for formal reasoning about relational properties of probabilistic programs, in particular for modeling reduction-based cryptographic proofs and for verifying differential privacy. In this paper, we demonstrate that probabilistic couplings can be used for verifying non-relational probabilistic properties. Specifically, we show that the program logic pRHL---whose proofs are formal versions of proofs by coupling---can be used for formalizing uniformity and probabilistic independence. We formally verify our main examples using the EasyCrypt proof assistant.
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cs.SE 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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Probabilistic Bisimulation for Parameterized Anonymity and Uniformity Verification
Anonymity and uniformity of parameterized probabilistic systems can be verified automatically by synthesizing regular bisimulation relations via automata learning and checking them in the decidable theory of regular structures.