Haonan Feng (Beijing University of Posts and Telecommunications), Hui Li (Beijing University of Posts and Telecommunications), Xuesong Pan (Beijing University of Posts and Telecommunications), Ziming Zhao (University at Buffalo)

The FIDO protocol suite aims at allowing users to log in to remote services with a local and trusted authenticator. With FIDO, relying services do not need to store user-chosen secrets or their hashes, which eliminates a major attack surface for e-business. Given its increasing popularity, it is imperative to formally analyze whether the security promises of FIDO hold. In this paper, we present a comprehensive and formal verification of the FIDO UAF protocol by formalizing its security assumptions and goals and modeling the protocol under different scenarios in ProVerif. Our analysis identifies the minimal security assumptions required for each of the security goals of FIDO UAF to hold. We confirm previously manually discovered vulnerabilities in an automated way and disclose several new attacks. Guided by the formal verification results we also discovered 2 practical attacks on 2 popular Android FIDO apps, which we responsibly disclosed to the vendors. In addition, we offer several concrete recommendations to fix the identified problems and weaknesses in the protocol.

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Towards Measuring Supply Chain Attacks on Package Managers for...

Ruian Duan (Georgia Institute of Technology), Omar Alrawi (Georgia Institute of Technology), Ranjita Pai Kasturi (Georgia Institute of Technology), Ryan Elder (Georgia Institute of Technology), Brendan Saltaformaggio (Georgia Institute of Technology), Wenke Lee (Georgia Institute of Technology)

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BaseSpec: Comparative Analysis of Baseband Software and Cellular Specifications...

Eunsoo Kim (KAIST), Dongkwan Kim (KAIST), CheolJun Park (KAIST), Insu Yun (KAIST), Yongdae Kim (KAIST)

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User Expectations and Understanding of Encrypted DNS Settings

Alexandra Nisenoff, Nick Feamster, Madeleine A Hoofnagle†, Sydney Zink. (University of Chicago and †Northwestern)

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FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data

Junjie Liang (The Pennsylvania State University), Wenbo Guo (The Pennsylvania State University), Tongbo Luo (Robinhood), Vasant Honavar (The Pennsylvania State University), Gang Wang (University of Illinois at Urbana-Champaign), Xinyu Xing (The Pennsylvania State University)

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