Lingbo Zhao (Institute of Information Engineering, Chinese Academy of Sciences), Yuhui Zhang (Institute of Information Engineering, Chinese Academy of Sciences), Zhilu Wang (Institute of Information Engineering, Chinese Academy of Sciences), Fengkai Yuan (Institute of Information Engineering, CAS), Rui Hou (Institute of Information Engineering, Chinese Academy of Sciences)

To evade existing antivirus software and detection systems, ransomware authors tend to obscure behavior differences with benign programs by imitating them or by weakening malicious behaviors during encryption. Existing defense solutions have limited effects on defending against evasive ransomware. Fortunately, through extensive observation, we find I/O behaviors of evasive ransomware exhibit a unique repetitiveness during encryption. This is rarely observed in benign programs. Besides, the $chi^2$ test and the probability distribution of byte streams can effectively distinguish encrypted files from benignly modified files. Inspired by these, we first propose ERW-Radar, a detection system, to detect evasive ransomware accurately and efficiently. We make three breakthroughs: 1) a contextual emph{Correlation} mechanism to detect malicious behaviors; 2) a fine-grained content emph{Analysis} mechanism to identify encrypted files; and 3) adaptive mechanisms to achieve a better trade-off between accuracy and efficiency. Experiments show that ERW-Radar detects evasive ransomware with an accuracy of 96.18% while maintaining a FPR of 5.36%. The average overhead of ERW-Radar is 5.09% in CPU utilization and 3.80% in memory utilization.

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NDSS Symposium 2025 Welcome and Opening Remarks

General Chairs: David Balenson, USC Information Sciences Institute and Heng Yin, University of California, Riverside Program Chairs: Christina Pöpper, New York University Abu Dhabi and Hamed Okhravi, MIT Lincoln Laboratory Artifact Evaluation Chairs: Daniele Cono D’Elia, Sapienza University and Mathy Vanhoef, KU Leuven

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Keynote talk by Prof. Gene Tsudik (University of California,...

Dr. Gene Tsudik, Distinguished Professor of Computer Science, University of California, Irvine

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Exploring User Perceptions of Security Auditing in the Web3...

Molly Zhuangtong Huang (University of Macau), Rui Jiang (University of Macau), Tanusree Sharma (Pennsylvania State University), Kanye Ye Wang (University of Macau)

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Crosstalk-induced Side Channel Threats in Multi-Tenant NISQ Computers

Ruixuan Li (Choudhury), Chaithanya Naik Mude (University of Wisconsin-Madison), Sanjay Das (The University of Texas at Dallas), Preetham Chandra Tikkireddi (University of Wisconsin-Madison), Swamit Tannu (University of Wisconsin, Madison), Kanad Basu (University of Texas at Dallas)

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