Cyber Times International Journal of Technology & Management

In this era of the information age, malware has turned into a genuine danger. Malware makers make such sort of malware which can harm the whole PC, spread over the system and  hack the mystery data and destroy the entire framework. Additionally, the expansive assortment of malware classes combined with their quick multiplication and polymorphic abilities and flaws of genuine information (clamor, missing qualities, and so on) keep on hindering the utilization of more advanced identification calculations. In this paper, we concentrate on investigating the use of machine learning strategies and abridged the ideas of recognition procedures connected to particular information in field of malware identification. Diverse information sources are additionally unmistakably portrayed here. Reviewed papers are condensed inside tables in view of the information utilized for identification reason. In this survey, a brief portrayal of information sources and how these are included in malware detection are specified well ordered. Our proposed approach concentrates on the utilizing continuous system information from an extensive Internet provider by selecting layer 3 and layer 4 network traffic features.