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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A Security Study about Electron Applications and a Programming...

Zihao Jin (Microsoft Research and Tsinghua University), Shuo Chen (Microsoft Research), Yang Chen (Microsoft Research), Haixin Duan (Tsinghua University and Quancheng Laboratory), Jianjun Chen (Tsinghua University and Zhongguancun Laboratory), Jianping Wu (Tsinghua University)

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Partitioning Ethereum without Eclipsing It

Hwanjo Heo (ETRI), Seungwon Woo (ETRI/KAIST), Taeung Yoon (KAIST), Min Suk Kang (KAIST), Seungwon Shin (KAIST)

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Trellis: Robust and Scalable Metadata-private Anonymous Broadcast

Simon Langowski (Massachusetts Institute of Technology), Sacha Servan-Schreiber (Massachusetts Institute of Technology), Srinivas Devadas (Massachusetts Institute of Technology)

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WIP: Augmenting Vehicle Safety With Passive BLE

Noah T. Curran (University of Michigan), Kang G. Shin (University of Michigan), William Hass (Lear Corporation), Lars Wolleschensky (Lear Corporation), Rekha Singoria (Lear Corporation), Isaac Snellgrove (Lear Corporation), Ran Tao (Lear Corporation)

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