Machine Learning and Deep Learning Methods for Cybersecurity

Yang Xin; Lingshuang Kong; Zhi Liu; Yuling Chen; Yanmiao Li; Hongliang Zhu; Mingcheng Gao; Haixia Hou; Chunhua Wang

doi:10.1109/access.2018.2836950

Abstract

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.

Keywords

Computer scienceKey (lock)Intrusion detection systemDeep learningArtificial intelligenceThe InternetNetwork securityMachine learningComputer securityIntrusionCyber threatsData scienceWorld Wide Web

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Publication Info

Year: 2018
Type: article
Volume: 6
Pages: 35365-35381
Citations: 1116
Access: Closed

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APA Style

                            
                                    Yang Xin, 
                                
                                    Lingshuang Kong, 
                                
                                    Zhi Liu
                                
                                et al.
                            
                            (2018). 
                            Machine Learning and Deep Learning Methods for Cybersecurity. 
                            IEEE Access
                            , 6
                            
                            , 35365-35381.
                            https://doi.org/10.1109/access.2018.2836950

Identifiers

DOI: 10.1109/access.2018.2836950