Abstract
Along with the rapid development of the IoT, the security issue of the IoT devices has also been greatly challenged. The variants of the IoT malware are constantly emerging. However, there is lacking of an IoT malware analysis architecture to extract and detect the malware behaviors. This paper addresses the problem and propose an IoT behavior analysis and detection architecture. We integrate the static and dynamic behavior analysis and network traffic analysis to understand and evaluate the IoT malware’s behaviors and spread range. The experiment on Mirai malware and several variants shows that the architecture is comprehensive and effective for the IoT malware behavior analysis as well as spread range monitoring.
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