Runze Zhang (Georgia Institute of Technology), Mingxuan Yao (Georgia Institute of Technology), Haichuan Xu (Georgia Institute of Technology), Omar Alrawi (Georgia Institute of Technology), Jeman Park (Kyung Hee University), Brendan Saltaformaggio (Georgia Institute of Technology)

For decades, law enforcement and commercial entities have attempted botnet takedowns with mixed success. These efforts, relying on DNS sink-holing or seizing C&C infrastructure, require months of preparation and often omit the cleanup of left-over infected machines. This allows botnet operators to push updates to the bots and re-establish their control. In this paper, we expand the goal of malware takedowns to include the covert and timely removal of frontend bots from infected devices. Specifically, this work proposes seizing the malware's built-in update mechanism to distribute crafted remediation payloads. Our research aims to enable this necessary but challenging remediation step after obtaining legal permission. We developed ECHO, an automated malware forensics pipeline that extracts payload deployment routines and generates remediation payloads to disable or remove the frontend bots on infected devices. Our study of 702 Android malware shows that 523 malware can be remediated via ECHO's takedown approach, ranging from covertly warning users about malware infection to uninstalling the malware.

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DiStefano: Decentralized Infrastructure for Sharing Trusted Encrypted Facts and...

Sofia Celi (Brave Software), Alex Davidson (NOVA LINCS & Universidade NOVA de Lisboa), Hamed Haddadi (Imperial College London & Brave Software), Gonçalo Pestana (Hashmatter), Joe Rowell (Information Security Group, Royal Holloway, University of London)

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Inspecting Compiler Optimizations on Mixed Boolean Arithmetic Obfuscation

Rachael Little, Dongpeng Xu (University of New Hampshire)

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Automated Mass Malware Factory: The Convergence of Piggybacking and...

Heng Li (Huazhong University of Science and Technology), Zhiyuan Yao (Huazhong University of Science and Technology), Bang Wu (Huazhong University of Science and Technology), Cuiying Gao (Huazhong University of Science and Technology), Teng Xu (Huazhong University of Science and Technology), Wei Yuan (Huazhong University of Science and Technology), Xiapu Luo (The Hong Kong Polytechnic University)

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Reinforcement Unlearning

Dayong Ye (University of Technology Sydney), Tianqing Zhu (City University of Macau), Congcong Zhu (City University of Macau), Derui Wang (CSIRO’s Data61), Kun Gao (University of Technology Sydney), Zewei Shi (CSIRO’s Data61), Sheng Shen (Torrens University Australia), Wanlei Zhou (City University of Macau), Minhui Xue (CSIRO's Data61)

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