Proving uniformity and independence by self-composition and coupling

19 pages•Published: May 4, 2017

Gilles Barthe, Thomas Espitau, Benjamin Grégoire, Justin Hsu and Pierre-Yves Strub

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.

Keyphrases: independence, probabilistic programs, program verification, relational logic, uniformity

In: Thomas Eiter and David Sands (editors). LPAR-21. 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning, vol 46, pages 385-403.

Links:	https://easychair.org/publications/paper/L9T5
	https://doi.org/10.29007/vz48

BibTeX entry

@inproceedings{LPAR-21:Proving_uniformity_independence_self,
  author    = {Gilles Barthe and Thomas Espitau and Benjamin Grégoire and Justin Hsu and Pierre-Yves Strub},
  title     = {Proving uniformity and independence by self-composition and coupling},
  booktitle = {LPAR-21. 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning},
  editor    = {Thomas Eiter and David Sands},
  series    = {EPiC Series in Computing},
  volume    = {46},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/L9T5},
  doi       = {10.29007/vz48},
  pages     = {385-403},
  year      = {2017}}

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