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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Detection and Resolution of Control Decision Anomalies

Prof. Kang Shin (Kevin and Nancy O'Connor Professor of Computer Science, and the Founding Director of the Real-Time Computing Laboratory (RTCL) in the Electrical Engineering and Computer Science Department at the University of Michigan)

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Scott Jordan (University of California, Irvine), Yoshimichi Nakatsuka (University of California, Irvine), Ercan Ozturk (University of California, Irvine), Andrew Paverd (Microsoft Research), Gene Tsudik (University of California, Irvine)

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MyTEE: Own the Trusted Execution Environment on Embedded Devices

Seungkyun Han (Chungnam National University), Jinsoo Jang (Chungnam National University)

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Smarter Contracts: Detecting Vulnerabilities in Smart Contracts with Deep...

Christoph Sendner (University of Wuerzburg), Huili Chen (University of California San Diego), Hossein Fereidooni (Technische Universität Darmstadt), Lukas Petzi (University of Wuerzburg), Jan König (University of Wuerzburg), Jasper Stang (University of Wuerzburg), Alexandra Dmitrienko (University of Wuerzburg), Ahmad-Reza Sadeghi (Technical University of Darmstadt), Farinaz Koushanfar (University of California San Diego)

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Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

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Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)