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Most behavioral detectors of malware remain specific to a given language and platform, mostly PE executables for Windows. The objective of this paper is to define a generic approach for behavioral detection based on two layers respectively responsible for abstraction and detection. The first abstraction layer remains specific to a platform and a language. This first layer interprets the collected instructions, API calls and arguments and classifies these operations as well as the involved objects according to their purpose in the malware lifecycle.
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