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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Alexander Warnecke (TU Braunschweig), Lukas Pirch (TU Braunschweig), Christian Wressnegger (Karlsruhe Institute of Technology (KIT)), Konrad Rieck (TU Braunschweig)

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Towards Automatic and Precise Heap Layout Manipulation for General-Purpose...

Runhao Li (National University of Defense Technology), Bin Zhang (National University of Defense Technology), Jiongyi Chen (National University of Defense Technology), Wenfeng Lin (National University of Defense Technology), Chao Feng (National University of Defense Technology), Chaojing Tang (National University of Defense Technology)

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Him of Many Faces: Characterizing Billion-scale Adversarial and Benign...

Shujiang Wu (Johns Hopkins University), Pengfei Sun (F5, Inc.), Yao Zhao (F5, Inc.), Yinzhi Cao (Johns Hopkins University)

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CANtropy: Time Series Feature Extraction-Based Intrusion Detection Systems for...

Md Hasan Shahriar, Wenjing Lou, Y. Thomas Hou (Virginia Polytechnic Institute and State University)

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