Predicted Packet Padding for Anonymous Web Browsing Against Traffic Analysis Attacks

Paper co-authored with Shui Yu and accepted for publication in IEEE Transactions on Information Forensics & Security.  The paper presents a novel method for padding web traffic to ensure a browser’s privacy.

Title: Predicted packet padding for anonymous web browsing against traffic analysis attacks

Authors: Yu, S., Zhao, G., Dou, W. and James, S.


Anonymous communication has become a hot re- search 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 defence 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 conducted extensive experiments on two real world data sets, and the results confirmed the advantage of the proposed method.


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