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Security protocols often use randomization to achieve probabilisticnon-determinism. This non-determinism, in turn, is used in obfuscating thedependence of observable values on secret data. Since the correctness ofsecurity protocols is very important, formal analysis of security protocols hasbeen widely studied in literature. Randomized security protocols have also beenanalyzed using formal techniques such as process-calculi and probabilisticmodel checking. In this paper, we consider the problem of validatingimplementations of randomized protocols. Unlike previous approaches which treatthe protocol as a white-box, our approach tries to verify an implementationprovided as a black box. Our goal is to infer the secrecy guarantees providedby a security protocol through statistical techniques. We learn theprobabilistic dependency of the observable outputs on secret inputs usingBayesian network. This is then used to approximate the leakage of secret. Inorder to evaluate the accuracy of our statistical approach, we compare ourtechnique with the probabilistic model checking technique on two examples:crowds protocol and dining crypotgrapher's protocol.

Statistical Analysis of Privacy and Anonymity Guarantees in Randomized Security Protocol Implementations