Review: Deep Learning Methods for Cybersecurity and Intrusion Detection Systems

• Main Authors: Macas, Mayra, Wu, Chunming
• Format: Journal Article
• Language: English
• Published: 04-12-2020
• Subjects: Computer Science - Cryptography and Security; Computer Science - Learning
• DOI: 10.48550/arxiv.2012.02891

As the number of cyber-attacks is increasing, cybersecurity is evolving to a
key concern for any business. Artificial Intelligence (AI) and Machine Learning
(ML) (in particular Deep Learning - DL) can be leveraged as key enabling
technologies for cyber-defense, since they can contribute in threat detection
and can even provide recommended actions to cyber analysts. A partnership of
industry, academia, and government on a global scale is necessary in order to
advance the adoption of AI/ML to cybersecurity and create efficient cyber
defense systems. In this paper, we are concerned with the investigation of the
various deep learning techniques employed for network intrusion detection and
we introduce a DL framework for cybersecurity applications.