Haohuang Wen (Ohio State University), Phillip Porras (SRI International), Vinod Yegneswaran (SRI International), Zhiqiang Lin (Ohio State University)

The short message service (SMS) is a cornerstone of modern smartphone communication that enables inter-personal text messaging and other SMS-based services (e.g., two-factor authentication). However, it can also be readily exploited to compromise unsuspecting remote victims. For instance, novel exploits such as Simjacker and WIBAttack enable transmission of binary SMS messages that could surreptitiously execute dangerous commands on a victim device. The SMS channel may also be subverted to drive other nefarious activities (e.g., spamming, DoS, and tracking), thereby undermining end-user security and privacy. Unfortunately, neither contemporary smartphone operating systems nor existing defense techniques provide a comprehensive bulwark against the spectrum of evolving SMS-driven threats. To address this limitation, we develop a novel defense framework called RILDEFENDER, which to the best of our knowledge is the first inline prevention system integrated into the radio interface layer (RIL) of Android smartphones. We describe an implementation of RILDEFENDER on three smartphone models with five Android versions of the Android Open Source Project (AOSP), and show that it is able to protect users from six types of SMS attacks spanning four adversary models. We evaluate RILDEFENDER against 19 reproduced SMS attacks and 11 contemporary SMS malware samples and find that RILDEFENDER detects all and automatically prevents all but one of these threats without affecting normal cellular operations.

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Understanding MPU Usage in Microcontroller-based Systems in the Wild

Wei Zhou, Zhouqi Jiang (School of Cyber Science and Engineering, Huazhong University of Science and Technology), Le Guan (School of Computing, University of Georgia)

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InfoMasker: Preventing Eavesdropping Using Phoneme-Based Noise

Peng Huang (Zhejiang University), Yao Wei (Zhejiang University), Peng Cheng (Zhejiang University), Zhongjie Ba (Zhejiang University), Li Lu (Zhejiang University), Feng Lin (Zhejiang University), Fan Zhang (Zhejiang University), Kui Ren (Zhejiang University)

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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)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

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)