Predicted packet padding for anonymous web browsing against traffic analysis attacks

Yu, Shui, Zhao, Guofeng, Dou, Wanchun and James, Simon 2012, Predicted packet padding for anonymous web browsing against traffic analysis attacks, IEEE transactions on information forensics and security, vol. 7, no. 4, pp. 1381-1393, doi: 10.1109/TIFS.2012.2197392.

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Title Predicted packet padding for anonymous web browsing against traffic analysis attacks
Author(s) Yu, ShuiORCID iD for Yu, Shui
Zhao, Guofeng
Dou, Wanchun
James, SimonORCID iD for James, Simon
Journal name IEEE transactions on information forensics and security
Volume number 7
Issue number 4
Start page 1381
End page 1393
Total pages 13
Publisher IEEE
Place of publication Piscataway, N. J.
Publication date 2012-08
ISSN 1556-6013
Keyword(s) anonymity
predicted packet padding
web browsing
Summary Anonymous communication has become a hot research topic in order to meet the increasing demand for web privacy protection. However, there are few such systems which can provide high level anonymity for web browsing. The reason is the current dominant dummy packet padding method for anonymization against traffic analysis attacks. This method inherits huge delay and bandwidth waste, which inhibits its use for web browsing. In this paper, we propose a predicted packet padding strategy to replace the dummy packet padding method for anonymous web browsing systems. The proposed strategy mitigates delay and bandwidth waste significantly on average. We formulated the traffic analysis attack and defense problem, and defined a metric, cost coefficient of anonymization (CCA), to measure the performance of anonymization. We thoroughly analyzed the problem with the characteristics of web browsing and concluded that the proposed strategy is better than the current dummy packet padding strategy in theory. We have conducted extensive experiments on two real world data sets, and the results confirmed the advantage of the proposed method.
Language eng
DOI 10.1109/TIFS.2012.2197392
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2012, IEEE
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Created: Mon, 13 Aug 2012, 12:59:58 EST

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