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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REDsec: Running Encrypted Discretized Neural Networks in Seconds

Lars Wolfgang Folkerts (University of Delaware), Charles Gouert (University of Delaware), Nektarios Georgios Tsoutsos (University of Delaware)

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BEAGLE: Forensics of Deep Learning Backdoor Attack for Better...

Siyuan Cheng (Purdue University), Guanhong Tao (Purdue University), Yingqi Liu (Purdue University), Shengwei An (Purdue University), Xiangzhe Xu (Purdue University), Shiwei Feng (Purdue University), Guangyu Shen (Purdue University), Kaiyuan Zhang (Purdue University), Qiuling Xu (Purdue University), Shiqing Ma (Rutgers University), Xiangyu Zhang (Purdue University)

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VulHawk: Cross-architecture Vulnerability Detection with Entropy-based Binary Code Search

Zhenhao Luo (College of Computer, National University of Defense Technology), Pengfei Wang (College of Computer, National University of Defense Technology), Baosheng Wang (College of Computer, National University of Defense Technology), Yong Tang (College of Computer, National University of Defense Technology), Wei Xie (College of Computer, National University of Defense Technology), Xu Zhou (College of Computer,…

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RR: A Fault Model for Efficient TEE Replication

Baltasar Dinis (Instituto Superior Técnico (IST-ULisboa) / INESC-ID / MPI-SWS), Peter Druschel (MPI-SWS), Rodrigo Rodrigues (Instituto Superior Técnico (IST-ULisboa) / INESC-ID)

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