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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Too Afraid to Drive: Systematic Discovery of Semantic DoS...

Ziwen Wan (University of California, Irvine), Junjie Shen (University of California, Irvine), Jalen Chuang (University of California, Irvine), Xin Xia (The University of California, Los Angeles), Joshua Garcia (University of California, Irvine), Jiaqi Ma (The University of California, Los Angeles), Qi Alfred Chen (University of California, Irvine)

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Characterizing the Adoption of Security.txt Files and their Applications...

William Findlay (Carleton University) and AbdelRahman Abdou (Carleton University)

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DRIVETRUTH: Automated Autonomous Driving Dataset Generation for Security Applications

Raymond Muller (Purdue University), Yanmao Man (University of Arizona), Z. Berkay Celik (Purdue University), Ming Li (University of Arizona) and Ryan Gerdes (Virginia Tech)

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Interpretable Federated Transformer Log Learning for Cloud Threat Forensics

Gonzalo De La Torre Parra (University of the Incarnate Word, TX, USA), Luis Selvera (Secure AI and Autonomy Lab, The University of Texas at San Antonio, TX, USA), Joseph Khoury (The Cyber Center For Security and Analytics, University of Texas at San Antonio, TX, USA), Hector Irizarry (Raytheon, USA), Elias Bou-Harb (The Cyber Center For…

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