Article ID Journal Published Year Pages File Type
4942715 Engineering Applications of Artificial Intelligence 2017 14 Pages PDF
Abstract
Contemporary malware makes wide use of techniques to evade popular detection approaches. Behavior-based detection is the most powerful approach to malware detection. This approach is based on system call sequences to model a malicious behavior. A recently immersed malware to defeat behavior-based detection approach is Multi-process malware. This malware is the consequence of multiple processes cooperating to fulfill a malicious task each of which performing a partition of main task and none of them shows an identifiable malicious behavior. In this paper, we have presented a new method called PbMMD for detecting Multi-process malware. In this method, we attempt to inspect the whole processes running on the system and discover collaborative processes by finding processes running along a common execution policy. Beforehand we have learned different execution policy by employing reinforcement algorithm. Finally we decide against a Multi-process malicious behavior by analyzing the cumulative behavior of identified collaborative processes.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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