Sandra Siby (EPFL), Marc Juarez (University of Southern California), Claudia Diaz (imec-COSIC KU Leuven), Narseo Vallina-Rodriguez (IMDEA Networks Institute), Carmela Troncoso (EPFL)

Virtually every connection to an Internet service is preceded by a DNS lookup which is performed without any traffic-level protection, thus enabling manipulation, redirection, surveillance, and censorship. To address these issues, large organizations such as Google and Cloudflare are deploying recently standardized protocols that encrypt DNS traffic between end users and recursive resolvers such as DNS-over-TLS (DoT) and DNS-over-HTTPS (DoH). In this paper, we examine whether encrypting DNS traffic can protect users from traffic analysis-based monitoring and censoring. We propose a novel feature set to perform the attacks, as those used to attack HTTPS or Tor traffic are not suitable for DNS’ characteristics. We show that traffic analysis enables the identification of domains with high accuracy in closed and open world settings, using 124 times less data than attacks on HTTPS flows. We find that factors such as location, resolver, platform, or client do mitigate the attacks performance but they are far from completely stopping them. Our results indicate that DNS-based censorship is still possible on encrypted DNS traffic. In fact, we demonstrate that the standardized padding schemes are not effective. Yet, Tor — which does not effectively mitigate traffic analysis attacks on web traffic— is a good defense against DoH traffic analysis.

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Zhongjie Wang (University of California, Riverside), Shitong Zhu (University of California, Riverside), Yue Cao (University of California, Riverside), Zhiyun Qian (University of California, Riverside), Chengyu Song (University of California, Riverside), Srikanth V. Krishnamurthy (University of California, Riverside), Kevin S. Chan (U.S. Army Research Lab), Tracy D. Braun (U.S. Army Research Lab)

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Milad Nasr (University of Massachusetts Amherst), Hadi Zolfaghari (University of Massachusetts Amherst), Amir Houmansadr (University of Massachusetts Amherst), Amirhossein Ghafari (University of Massachusetts Amherst)

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Yanzi Zhu (UC Santa Barbara), Zhujun Xiao (University of Chicago), Yuxin Chen (University of Chicago), Zhijing Li (UC Santa Barbara), Max Liu (University of Chicago), Ben Y. Zhao (University of Chicago), Heather Zheng (University of Chicago)

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Finding Safety in Numbers with Secure Allegation Escrows

Venkat Arun (Massachusetts Institute of Technology), Aniket Kate (Purdue University), Deepak Garg (Max Planck Institute for Software Systems), Peter Druschel (Max Planck Institute for Software Systems), Bobby Bhattacharjee (University of Maryland)

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