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Malware detection and classification is critical for the security of IT infrastructure. Legacy detection of malware has been highly reliant on static signatures, so malware authors have evolved code polymorphic techniques to counteract these tools, thus rendering static malware detectors ineffective. While malware writers may easily use code rewriting techniques to scramble binary images; malware...
Malware infection trees are computational structures for analyzing and identifying different processes and files during the execution of malware. In this paper, we describe a sandboxing-based formalization to predict malware behaviors such as the possibility of file and process creation. Model checking is used as a querying mechanism on a labeled transition system representing a malware infection...
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