A review of deep learning applied to cybersecurity

Abstract

This study conceives to present an overview of cybersecurity from the perspective of neural networks and deep learning techniques according to the diverse current needs in computer security environments. It also discusses the applicability of these techniques in various cybersecurity works, such as intrusion detection, malware or botnet identification, phishing, cyber-attack prediction, denial of service, cyber anomalies, etc. In conclusion, four algorithms applicable to Cybersecurity are highlighted and recommended as a knowledge base and facility for future research within the scope of our study in the field. The ultimate target of this research is to serve as a reference point and guide for academia and practitioners in cybersecurity industries from the deep learning point of view.