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An important yet largely uncharted problem in malware defense is how to automate generation of infection signatures for detecting compromised systems, i.e., signatures that characterize the behavior of malware residing on a system. To this end, the authors develop AGIS, the first host-based technique that detects infections by novel malware and automatically generates an infection signature of the malware. AGIS monitors the run-time behavior of suspicious code according to a set of security policies to detect a previously undetected infection, and then identifies its characteristic behavior in terms of system or API calls.
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