Chapter 10 - Contemporary survey on effectiveness of machine and deep learning techniques for cyber security

Abstract

Machine learning (ML) and deep learning (DL) techniques are applied in a broad range of application fields where it proves its supremacy over other methods. ML and DL techniques can be effectively integrated with cyber security systems to improve security measures within an organization. The majority of the ML and DL applications are adapted toward fields like marketing, sales, and finance, and used for the purpose of protecting the business or products from malware and hacker attacks. Efficient strategies for intrusion detection, malicious code analysis, and forensic identification are critical because cybercrime continues to be a growing concern in terms of protection and privacy concerns. This book chapter discusses how machine and deep learning approaches can be used to advance cyber security goals such as identification, modeling, tracking, and analysis, as well as protection against various threats to sensitive data and security systems. Then some recent related research papers are summarized and analyzed based on the methodologies used. Finally, future scope for research topics that include the various cyber security issues can be addressed and solved using ML and DL methods.