Malware Detection Using Online Information Sharing Platforms and Behavior Based Analysis
Proceedings of 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT), 2018 held at Malaviya National Institute of Technology, Jaipur (India) on March 26-27, 2018
4 Pages Posted: 9 May 2018
Date Written: April 28, 2018
The recent years have seen many cyber attacks that left people bewitched. The malwares are evolving everyday rendering the traditional anti-viruses useless. This paper deals with an approach that identifies and detects any potential threat to the system by using community based information sharing platform and behavior based malware detection using machine learning. Out of several options available, the two feasible options chosen were – VirusTotal and MISP. For signature based detection, the project uses MD5 hashes of the given file. Once the MD5 has been extracted it goes through an event search on MISP and VirusTotal; if any event is reported for the same, the file is considered malicious. And for the behavior based malware detection, multiple machine learning algorithms are used and the best one is chosen on the basis of accuracy.
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