Mohit Kumar Jangid (The Ohio State University), Yue Zhang (Computer Science & Engineering, Ohio State University), Zhiqiang Lin (The Ohio State University)

Bluetooth is a leading wireless communication technology used by billions of Internet of Things (IoT) devices today. Its ubiquity demands systematic security scrutiny. A key ingredient in Bluetooth security is secure pairing, which includes Numeric comparison (NC) and Passkey Entry (PE). However, most prior formal efforts have considered only NC, and PE has not yet been formally studied in depth. In this paper, we propose a detailed formal analysis of the PE protocol. In particular, we present a generic formal model, built using Tamarin, to verify the security of PE by precisely capturing the protocol behaviors and attacker capabilities. Encouragingly, it rediscovers three known attacks (confusion attacks, static passcode attacks, and reflection attacks), and more importantly, also uncovers two new attacks (group guessing attacks and ghost attacks) spanning across diverse attack vectors (e.g., static variable reuse, multi-threading, reflection, human error, and compromise device). Finally, after applying fixes to each vulnerability, our model further proves the confidentiality and authentication properties of the PE protocol using an inductive base model.

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Assessing the Impact of Interface Vulnerabilities in Compartmentalized Software

Hugo Lefeuvre (The University of Manchester), Vlad-Andrei Bădoiu (University Politehnica of Bucharest), Yi Chen (Rice University), Felipe Huici (Unikraft.io), Nathan Dautenhahn (Rice University), Pierre Olivier (The University of Manchester)

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PPA: Preference Profiling Attack Against Federated Learning

Chunyi Zhou (Nanjing University of Science and Technology), Yansong Gao (Nanjing University of Science and Technology), Anmin Fu (Nanjing University of Science and Technology), Kai Chen (Chinese Academy of Science), Zhiyang Dai (Nanjing University of Science and Technology), Zhi Zhang (CSIRO's Data61), Minhui Xue (CSIRO's Data61), Yuqing Zhang (University of Chinese Academy of Science)

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dewolf: Improving Decompilation by leveraging User Surveys

Steffen Enders, Eva-Maria C. Behner, Niklas Bergmann, Mariia Rybalka, Elmar Padilla (Fraunhofer FKIE, Germany), Er Xue Hui, Henry Low, Nicholas Sim (DSO National Laboratories, Singapore)

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