A Survey of Deep Learning Methods for Cyber Security 论文
2019Information引用 544顶会
Network Security and Intrusion DetectionAdvanced Malware Detection TechniquesInternet Traffic Analysis and Secure E-voting
详细信息
- 发表期刊/会议
- Information
- 发表日期
- 2019-04-02
- 发表年份
- 2019
关键词
Network Security and Intrusion DetectionAdvanced Malware Detection TechniquesInternet Traffic Analysis and Secure E-voting
摘要
This survey paper describes a literature review of deep learning (DL) methods for cyber security applications. A short tutorial-style description of each DL method is provided, including deep autoencoders, restricted Boltzmann machines, recurrent neural networks, generative adversarial networks, and several others. Then we discuss how each of the DL methods is used for security applications. We cover a broad array of attack types including malware, spam, insider threats, network intrusions, false data injection, and malicious domain names used by botnets.