Abstract
Website fingerprinting enables eavesdroppers to identify the website a user is visiting by network surveillance, even if the traffic is protected by anonymous communication technologies such as Tor. To defend against website fingerprinting attacks, Tor provides a circuit padding framework as the official way to implement padding defenses. However, the circuit padding framework can not support additional delay, which makes most defense schemes unworkable. In this paper, we study the patterns of HTTP requests and responses generated during website loading and analyze how these high-level features correlate with the underlying features of network traffic. We find that the HTTP requests sent and responses received continuously in a short period of time, which we call HTTP burst, have a significant impact on network traffic. Then we propose a novel website fingerprinting defense algorithm, Advanced Adaptive Padding(AAP). The design principle of AAP is similar to Adaptive Padding, which works by obfuscating burst features. AAP does not delay application packets and is in line with the design philosophy of low latency networks such as Tor. Besides, AAP uses a more sensible traffic obfuscation strategy, which makes it more effective. Experiments show that AAP outperforms other zero-delay defenses with moderate bandwidth overhead.
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Acknowledgment
This work was supported inpart by the National Natural Science Foundation of China (61972219), the Research and Development Program of Shenzhen (JCYJ20190813174403598), the Overseas Research Cooperation Fund of Tsinghua Shenzhen International Graduate School (HW2021013), the Youth Innovation Promotion Association CAS (2019163), the Guangdong Basic and Applied Basic Research Foundation (2022A1515010417), the Key Project of Shenzhen Municipality(JSGG20211029095545002), the Science and Technology Research Project of Henan Province(222102210096), the Key Laboratory of Network Assessment Technology, Institute of Information Engineering, Chinese Academy of Sciences, and Shenzhen Science and Technology Innovation Commission (Research Center for Computer Network (Shenzhen) Ministry of Education).
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Yang, Z., Xiao, X., Zhang, B., Hu, G., Li, Q., Liu, Q. (2023). AAP: Defending Against Website Fingerprinting Through Burst Obfuscation. In: Yang, X., et al. Advanced Data Mining and Applications. ADMA 2023. Lecture Notes in Computer Science(), vol 14180. Springer, Cham. https://doi.org/10.1007/978-3-031-46677-9_8
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