Deep learning

Cover (algebra)

Mathematics

Domain (mathematical analysis)

The Internet

World Wide Web

Machine learning

Engineering

Mathematical analysis

Political science

Artificial intelligence

Boltzmann machine

Botnet

Network security

Insider

Computer science

Malware

Adversarial system

Computer security

Artificial neural network

Mechanical engineering

Information

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.

A Survey of Deep Learning Methods for Cyber Security