Anonymity analysis of mix networks against flow-correlation attacks

Mix networks are designed to provide anonymity for users in a variety of applications, including anonymous Web browsing and numerous E-commerce systems. Such networks have been shown to be susceptible to flow correlation attacks empirically. In this paper, we model the effectiveness of flow correlation attacks. Our results illustrate the quantitative relationship among system parameters such as sample size, noise level, payload flow rate, and detection rate. Our analysis quantitatively predicts how existing flow-based anonymous systems would fail under flow-correlation attacks, thus providing useful guidelines for the design of future anonymous systems.