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Title: CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples
We propose CheckDP, an automated and integrated approach for proving or disproving claims that a mechanism is differentially private. CheckDP can find counterexamples for mechanisms with subtle bugs for which prior counterexample generators have failed. Furthermore, it was able to automatically generate proofs for correct mechanisms for which no formal verification was reported before. CheckDP is built on static program analysis, allowing it to be more efficient and precise in catching infrequent events than sampling based counterexample generators (which run mechanisms hundreds of thousands of times to estimate their output distribution). Moreover, its sound approach also allows automatic verification of correct mechanisms. When evaluated on standard benchmarks and newer privacy mechanisms, CheckDP generates proofs (for correct mechanisms) and counterexamples (for incorrect mechanisms) within 70 seconds without any false positives or false negatives.  more » « less
Award ID(s):
1702760
NSF-PAR ID:
10251222
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
CCS '20: Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security
Page Range / eLocation ID:
919 to 938
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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