Hao Zhou (The Hong Kong Polytechnic University), Haoyu Wang (Beijing University of Posts and Telecommunications), Xiapu Luo (The Hong Kong Polytechnic University), Ting Chen (University of Electronic Science and Technology of China), Yajin Zhou (Zhejiang University), Ting Wang (Pennsylvania State University)

Due to the complexity resulted from the huge code base and the multi-context nature of Android, inconsistent access control enforcement exists in Android, which can be exploited by malware to bypass the access control and perform unauthorized security-sensitive operations. Unfortunately, existing studies only focus on the inconsistent access control enforcement in the Java context of Android. In this paper, we conduct the first systematic investigation on the inconsistent access control enforcement across the Java context and native context of Android. In particular, to automatically discover cross-context inconsistencies, we design and implement IAceFinder, a new tool that extracts and contrasts the access control enforced in the Java context and native context of Android. Applying IAceFinder to 14 open-source Android ROMs, we find that it can effectively uncover their cross-context inconsistent access control enforcement. Specifically, IAceFinder discovers 23 inconsistencies that can be abused by attackers to compromise the device and violate user privacy.

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“So I Sold My Soul“: Effects of Dark Patterns...

Oksana Kulyk (ITU Copenhagen), Willard Rafnsson (IT University of Copenhagen), Ida Marie Borberg, Rene Hougard Pedersen

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P4DDPI: Securing P4-Programmable Data Plane Networks via DNS Deep...

Ali AlSabeh (University of South Carolina), Elie Kfoury (University of South Carolina), Jorge Crichigno (University of South Carolina) and Elias Bou-Harb (University of Texas at San Antonio)

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Titanium: A Metadata-Hiding File-Sharing System with Malicious Security

Weikeng Chen (DZK/UC Berkeley), Thang Hoang (Virginia Tech), Jorge Guajardo (Robert Bosch Research and Technology Center), Attila A. Yavuz (University of South Florida)

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Demo #13: Attacking LiDAR Semantic Segmentation in Autonomous Driving

Yi Zhu (State University of New York at Buffalo), Chenglin Miao (University of Georgia), Foad Hajiaghajani (State University of New York at Buffalo), Mengdi Huai (University of Virginia), Lu Su (Purdue University) and Chunming Qiao (State University of New York at Buffalo)

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