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Countering Statistical Disclosure with Receiver-Bound Cover Traffic

Nayantara MalleshContact Information and Matthew WrightContact Information

(1)  Department of Computer Science and Engineering, The University of Texas at Arlington,  
Abstract
Anonymous communications provides an important privacy service by keeping passive eavesdroppers from linking communicating parties. However, using long-term statistical analysis of traffic sent to and from such a system, it is possible to link senders with their receivers. Cover traffic is an effective, but somewhat limited, counter strategy against this attack. Earlier work in this area proposes that privacy-sensitive users generate and send cover traffic to the system. However, users are not online all the time and cannot be expected to send consistent levels of cover traffic, drastically reducing the impact of cover traffic. We propose that the mix generate cover traffic that mimics the sending patterns of users in the system. This receiver-bound cover helps to make up for users that aren’t there, confusing the attacker. We show through simulation how this makes it difficult for an attacker to discern cover from real traffic and perform attacks based on statistical analysis. Our results show that receiver-bound cover substantially increases the time required for these attacks to succeed. When our approach is used in combination with user-generated cover traffic, the attack takes a very long time to succeed.

Keywords  privacy-enhancing technologies - cover traffic - anonymity


Contact Information Nayantara Mallesh
Email: nayantara.mallesh@uta.edu
URL: http://isec.uta.edu

Contact Information Matthew Wright
Email: mwright@uta.edu
URL: http://isec.uta.edu
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