Vik Vanderlinden, Wouter Joosen, Mathy Vanhoef (imec-DistriNet, KU Leuven)

Performing a remote timing attack typically entails the collection of many timing measurements in order to overcome noise due to network jitter. If an attacker can reduce the amount of jitter in their measurements, they can exploit timing leaks using fewer measurements. To reduce the amount of jitter, an attacker may use timing information that is made available by a server. In this paper, we exploit the use of the server-timing header, which was created for performance monitoring and in some cases exposes millisecond accurate information about server-side execution times. We show that the header is increasingly often used, with an uptick in adoption rates in recent months. The websites that use the header often host dynamic content of which the generation time can potentially leak sensitive information. Our new attack techniques, one of which collects the header timing values from an intermediate proxy, improve performance over standard attacks using roundtrip times. Experiments show that, overall, our new attacks (significantly) decrease the number of samples required to exploit timing leaks. The attack is especially effective against geographically distant servers.

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Let Me Unwind That For You: Exceptions to Backward-Edge...

Victor Duta (Vrije Universiteit Amsterdam), Fabian Freyer (University of California San Diego), Fabio Pagani (University of California, Santa Barbara), Marius Muench (Vrije Universiteit Amsterdam), Cristiano Giuffrida (Vrije Universiteit Amsterdam)

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Detecting Tor Bridge from Sampled Traffic in Backbone Networks

Hua Wu (School of Cyber Science & Engineering and Key Laboratory of Computer Network and Information Integration Southeast University, Ministry of Education, Jiangsu Nanjing, Purple Mountain Laboratories for Network and Communication Security (Nanjing, Jiangsu)), Shuyi Guo, Guang Cheng, Xiaoyan Hu (School of Cyber Science & Engineering and Key Laboratory of Computer Network and Information Integration…

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Work-in-Progress: Detecting Browser-in-the-Browser Attacks from Their Behaviors and DOM...

Ryusei Ishikawa, Soramichi Akiyama, and Tetsutaro Uehara (Ritsumeikan University)

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BARS: Local Robustness Certification for Deep Learning based Traffic...

Kai Wang (Tsinghua University), Zhiliang Wang (Tsinghua University), Dongqi Han (Tsinghua University), Wenqi Chen (Tsinghua University), Jiahai Yang (Tsinghua University), Xingang Shi (Tsinghua University), Xia Yin (Tsinghua University)

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