Machine Learning and Deep Learning Methods for Cybersecurity

With the development of the Internet, cyber-attacks are changing rapidly and the cyber security situation is not optimistic. This survey report describes key literature surveys on machine learning (ML) and deep learning (DL) methods for network analysis of intrusion detection and provides a brief tu...

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Bibliographic Details
Published in:IEEE access 2018-01, Vol.6, p.35365-35381
Main Authors: Xin, Yang, Kong, Lingshuang, Liu, Zhi, Chen, Yuling, Li, Yanmiao, Zhu, Hongliang, Gao, Mingcheng, Hou, Haixia, Wang, Chunhua
Format: Article
Language:English
Subjects:
Computer security
Cybersecurity
Deep learning
Feature extraction
Intrusion detection
Literature reviews
Machine learning
Machine learning algorithms
Network analysis
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Summary:With the development of the Internet, cyber-attacks are changing rapidly and the cyber security situation is not optimistic. This survey report describes key literature surveys on machine learning (ML) and deep learning (DL) methods for network analysis of intrusion detection and provides a brief tutorial description of each ML/DL method. Papers representing each method were indexed, read, and summarized based on their temporal or thermal correlations. Because data are so important in ML/DL methods, we describe some of the commonly used network datasets used in ML/DL, discuss the challenges of using ML/DL for cybersecurity and provide suggestions for research directions.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2836950