Int. J. of Granular Computing, Rough Sets and Intelligent Systems   »   2015 Vol.4, No.1

 

 

Title: An improved statistical disclosure attack

 

Authors: Bin Tang; Rajiv Bagai; Huabo Lu

 

Addresses:
Department of Computer Science, California State University Dominguez Hills, Carson, CA, USA
Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA
Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA

 

Abstract: Statistical disclosure attack (SDA) is known to be an effective long-term intersection attack against mix-based anonymising systems, in which an attacker observes a large volume of the incoming and outgoing traffic of a system and correlates its senders with receivers that they often send messages to. In this paper, we further strengthen the effectiveness of this attack. We show, by both an example and a proof, that by employing a weighted mean of the observed relative receiver popularity, the attacker can determine more accurately the set of receivers that a user sends messages to, than by using the existing arithmetic mean-based technique.

 

Keywords: statistical disclosure attack; SDA; anonymity; traffic analysis; security; intersection attacks.

 

DOI: 10.1504/IJGCRSIS.2015.074731

 

Int. J. of Granular Computing, Rough Sets and Intelligent Systems, 2015 Vol.4, No.1, pp.30 - 38

 

Submission date: 14 Apr 2015
Date of acceptance: 12 Jun 2015
Available online: 16 Feb 2016

 

 

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