Efficient, Effective, and Realistic Website Fingerprinting Mitigation

• Main Authors: Weiqi Cui, Jiangmin Yu, Yanmin Gong, Eric Chan-Tin
• Format: Article
• Language: English
• Published: European Alliance for Innovation (EAI) 2019-04-01
• Series: EAI Endorsed Transactions on Security and Safety
• Subjects: privacy; noise; website fingerprinting; cover traffic
• Online Access: https://eudl.eu/pdf/10.4108/eai.29-1-2019.161977

Website fingerprinting attacks have been shown to be able to predict the website visited even if the networkconnection is encrypted and anonymized. These attacks have achieved accuracies as high as 92%. Mitigations to these attacks are using cover/decoy network traffic to add noise, padding to ensure all the network packets are the same size, and introducing network delays to confuse an adversary. Although these mitigations have been shown to be effective, reducing the accuracy to 10%, the overhead is high. The latency overhead is above 100% and the bandwidth overhead is at least 30%. We introduce a new realistic cover traffic algorithm, based on a user’s previous network traffic, to mitigate website fingerprinting attacks. In simulations, our algorithmreduces the accuracy of attacks to 14% with zero latency overhead and about 20% bandwidth overhead. In real-world experiments, our algorithms reduces the accuracy of attacks to 16% with only 20% bandwidthoverhead.