website fingerprinting in onion routing based anonymization networks
Low-latency anonymization networks such as Tor and JAP claim to hide the recipient and the content of communications from a local observer, i.e., an entity that can eavesdrop the traffic between the user and the first anonymization node. Especially users in totalitarian regimes strongly depend on such networks to freely communicate. For these people, anonymity is particularly important and an analysis of the anonymization methods against various attacks is necessary to ensure adequate protection. In this paper we show that anonymity in Tor and JAP is not as strong as expected so far and cannot resist website fingerprinting attacks under certain circumstances. We first define features for website fingerprinting solely based on volume, time, and direction of the traffic. As a result, the subsequent classification becomes much easier. We apply support vector machines with the introduced features. We are able to improve recognition results of existing works on a given state-of-the-art dataset in Tor from 3\% to 55\% and in JAP from 20\% to 80\%. The datasets assume a closed-world with 775 websites only. In a next step, we transfer our findings to a more complex and realistic open-world scenario, i.e., recognition of several websites in a set of thousands of random unknown websites. To the best of our knowledge, this work is the first successful attack in the open-world scenario. We achieve a surprisingly high true positive rate of up to 73\% for a false positive rate of 0.05\%. Finally, we show preliminary results of a proof-of-concept implementation that applies camouflage as a countermeasure to hamper the fingerprinting attack. For JAP, the detection rate decreases from 80\% to 4\% and for Tor it drops from 55\% to about 3\%.
website fingerprinting anonymous communication pattern recognition privacy traffic analysis