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In order to detect malicious file system activity, some commercial and academic anti-ransomware solutions implement deception-based techniques, specifically by placing decoy files among user files. While this approach raises the bar against current ransomware, as any access to a decoy file is a sign of malicious activity, the robustness of decoy strategies has not been formally analyzed and fully tested. In this paper, we analyze existing decoy strategies and discuss how they are effective in countering current ransomware by defining a set of metrics to measure their robustness. To demonstrate how ransomware can identify existing deception-based detection strategies, we have implemented a proof-of-concept anti-decoy ransomware that successfully bypasses decoys by using a decision engine with few rules. Finally, we discuss existing issues in decoy-based strategies and propose practical solutions to mitigate them.
: Computer science [C05] [Engineering, computing & technology], Deception, Ransomware, Cryptographic, Decoy, : Sciences informatiques [C05] [Ingénierie, informatique & technologie], Malware
: Computer science [C05] [Engineering, computing & technology], Deception, Ransomware, Cryptographic, Decoy, : Sciences informatiques [C05] [Ingénierie, informatique & technologie], Malware
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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