Open AccessMachine Learning for Analyzing Malware
Author(s) -
Zhenyan Liu,
Yifei Zeng,
Yida Yan,
Pengfei Zhang,
Yong Wang
Publication year - 2017
Publication title -
journal of cyber security and mobility
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.198
H-Index - 9
eISSN - 2245-4578
pISSN - 2245-1439
DOI - 10.13052/2245-1439.631
Subject(s) - malware , computer science , malware analysis , feature selection , cluster analysis , machine learning , artificial intelligence , the internet , selection (genetic algorithm) , process (computing) , phishing , feature (linguistics) , feature extraction , data mining , computer security , world wide web , linguistics , philosophy , operating system
The Internet has become an indispensable part of people’s work and life, but it also provides favorable communication conditions for malwares. Therefore, malwares are endless and spread faster and become one of the main threats of current network security. Based on the malware analysis process, from the original feature extraction and feature selection to malware analysis, this paper introduces the machine learning algorithms such as classification, clustering and association analysis, and how to use these machine learning algorithms to effectively analyze the malware and its variants.