Meet the Family of Statistical Disclosure Attacks

TL;DR

This paper presents a comprehensive framework for comparing various statistical disclosure attacks in anonymous communication systems, introducing new methods and analyzing their effectiveness and relation to existing attacks.

Contribution

It introduces a unified framework for the SDA family, proposes two new attack variants, and compares their performance with LSDA, advancing understanding of attack effectiveness.

Findings

Proposed methods significantly improve SDA performance.

LSDA outperforms SDA family with sufficient observations.

Empirical analysis of attack performance under different system parameters.

Abstract

Disclosure attacks aim at revealing communication patterns in anonymous communication systems, such as conversation partners or frequency. In this paper, we propose a framework to compare between the members of the statistical disclosure attack family. We compare different variants of the Statistical Disclosure Attack (SDA) in the literature, together with two new methods; as well as show their relation with the Least Squares Disclosure Attack (LSDA). We empirically explore the performance of the attacks with respect to the different parameters of the system. Our experiments show that i) our proposals considerably improve the state-of-the-art SDA and ii) confirm that LSDA outperforms the SDA family when the adversary has enough observations of the system.