Open AccessA Survey on Feature Extraction Methods of Heuristic Malware Detection
Author(s) -
Nuannuan Li,
Zheng Zhang,
Xin Che,
Zhimin Guo,
Junfei Cai
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1757/1/012071
Subject(s) - malware , computer science , hacker , heuristic , signature (topology) , the internet , feature (linguistics) , computer security , artificial intelligence , feature extraction , machine learning , data mining , cryptovirology , world wide web , mathematics , linguistics , philosophy , geometry
In the age of the Internet, while the network is sending a lot of information to people, hackers also transmit a lot of malicious code through the network. Hackers use these malicious codes to steal sensitive information from infected people and damage machines and devices to achieve their evil goals. Therefore, it is very important to accurately detect malware to protect users from loss. There are now three major methods of detecting malware, which are signature-based, behavior-based, and heuristic-based methods. However, with the rapid increase in the types and number of malware, signature -based method can’t detect unknown malware and behavior-based cannot guarantee the False Positive Ratio. So these detection methods can no longer meet the needs. Therefore, some researchers proposed some heuristic-based detection methods. In this article we overview the methods used to extract features and the features extracted in heuristic detection and discuss the advantages and disadvantages of the features