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

TL;DR

This paper introduces a statistical method using Bayesian networks to validate the secrecy guarantees of randomized security protocol implementations in a black-box setting, complementing formal verification techniques.

Contribution

It presents a novel statistical approach for analyzing implementation-level security guarantees of randomized protocols without requiring white-box access.

Findings

The Bayesian network approach accurately estimates secret leakage.

The method effectively compares with probabilistic model checking.

It provides a practical tool for black-box security analysis.

Abstract

Security protocols often use randomization to achieve probabilistic non-determinism. This non-determinism, in turn, is used in obfuscating the dependence of observable values on secret data. Since the correctness of security protocols is very important, formal analysis of security protocols has been widely studied in literature. Randomized security protocols have also been analyzed using formal techniques such as process-calculi and probabilistic model checking. In this paper, we consider the problem of validating implementations of randomized protocols. Unlike previous approaches which treat the protocol as a white-box, our approach tries to verify an implementation provided as a black box. Our goal is to infer the secrecy guarantees provided by a security protocol through statistical techniques. We learn the probabilistic dependency of the observable outputs on secret inputs using Bayesian network. This is then used to approximate the leakage of secret. In order to evaluate the accuracy of our statistical approach, we compare our technique with the probabilistic model checking technique on two examples: crowds protocol and dining crypotgrapher's protocol.