Meet the Family of Statistical Disclosure Attacks
This work addresses security vulnerabilities in anonymous communication systems, but it is incremental as it builds on existing attack families.
The paper tackles the problem of comparing and improving statistical disclosure attacks for revealing communication patterns in anonymous systems, showing that their new methods significantly improve state-of-the-art SDA and confirming LSDA's superiority with sufficient observations.
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.