A Review on Application of GANs in Cybersecurity Domain

Cybersecurity is essential to protect the tremendous increase in data stored on servers and its transmission on networks. The techniques used to detect threats and preserve data need to be updated regularly to prevent advanced attacks in the future. The information transferred over a network is converted into unintelligible data using codes and cyphers to achieve data integrity and confidentiality. At present, a firewall is used to block unknown traffic, antimalware software to detect viruses, trojan, worms and intrusion detection systems to detect attacks. The security professionals are employing Generative Adversarial Networks (GANs) to produce amazing results in fields such as Intrusion Detection, Steganography, Password Cracking, and Anomaly Generation. This paper presents a systematic literature review of GANs applications in the cybersecurity domain, including analysis of specific extended GAN frameworks and currently used stable cybersecurity datasets.