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.

网络安全对于保护存储在服务器上的大量数据及其在网络上的传输至关重要。用于检测威胁和保存数据的技术需要定期更新，以防止未来的高级攻击。通过网络传输的信息使用代码和密码转换为难以理解的数据，以实现数据的完整性和机密性。目前，防火墙用于阻止未知流量，反恶意软件用于检测病毒，木马、蠕虫和入侵检测系统用于检测攻击。安全专家正在使用生成对抗网络 (GAN) 在入侵检测、隐写术、密码破解和异常生成等领域产生惊人的结果。