A Reference Model for Information Security Applications of Generative Adversarial Network Variants

Information security stemming from Generative Adversarial Network (GAN) variants has garnered significant attention. However, a complete reference model targeting this security problem has yet to be established. This paper selects several GAN variants as the research subject and proposes a reference model framework for the information security applications of adversarial generative network variants. The proposed framework is derived using the NIST information security reference model methodology. By conducting a comprehensive analysis of the structure and information security risks of GAN variants, this paper classifies information security attacks on information systems of GAN variants into three categories and maps them onto the security target reference model. The resulting security application reference model can serve as a basis and reference for improving system confidentiality, integrity, and availability, as well as facilitating the design, analysis, and verification of security against malicious attacks. Moreover, the research method employed in this paper is also applicable to information security research of other types of information systems. Therefore, the proposed reference model framework can serve as a valuable contribution to the field of information security and advance the development of effective countermeasures against adversarial generative network variants.