Takuya Watanabe (NTT), Eitaro Shioji (NTT), Mitsuaki Akiyama (NTT), Tatsuya Mori (Waseda University, NICT, and RIKEN AIP)

Intermediary web services such as web proxies, web translators, and web archives have become pervasive as a means to enhance the openness of the web. These services aim to remove the intrinsic obstacles to web access; i.e., access blocking, language barriers, and missing web pages. In this study, we refer to these services as web rehosting services and make the first exploration of their security flaws. The web rehosting services use a single domain name to rehost several websites that have distinct domain names; this characteristic makes web rehosting services intrinsically vulnerable to violating the same origin policy if not operated carefully. Based on the intrinsic vulnerability of web rehosting services, we demonstrate that an attacker can perform five different types of attacks that target users who make use of web rehosting services: persistent man-in-the-middle attack, abusing privileges to access various resources, stealing credentials, stealing browser history, and session hijacking/injection. Our extensive analysis of 21 popular web rehosting services, which have more than 200 million visits per day, revealed that these attacks are feasible. In response to this observation, we provide effective countermeasures against each type of attack.

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Locally Differentially Private Frequency Estimation with Consistency

Tianhao Wang (Purdue University), Milan Lopuhaä-Zwakenberg (Eindhoven University of Technology), Zitao Li (Purdue University), Boris Skoric (Eindhoven University of Technology), Ninghui Li (Purdue University)

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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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Post-Quantum Authentication in TLS 1.3: A Performance Study

Dimitrios Sikeridis (The University of New Mexico), Panos Kampanakis (Cisco Systems), Michael Devetsikiotis (The University of New Mexico)

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BLAZE: Blazing Fast Privacy-Preserving Machine Learning

Arpita Patra (Indian Institute of Science, Bangalore), Ajith Suresh (Indian Institute of Science, Bangalore)

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