Generative Adversarial Network Based Approach towards Synthetically Generating Insider Threat Scenarios  

作　　者：Mayesh Mohapatra Anshumaan Phukan Vijay K. Madisetti Mayesh Mohapatra;Anshumaan Phukan;Vijay K. Madisetti(Indian Institute of Science, Bengaluru, India;Bennett University, Greater Noida, India;School of Cybersecurity and Privacy, Georgia Institute of Technology, Atlanta, USA)

机构地区：[1]Indian Institute of Science, Bengaluru, India [2]Bennett University, Greater Noida, India [3]School of Cybersecurity and Privacy, Georgia Institute of Technology, Atlanta, USA

出　　处：《Journal of Software Engineering and Applications》2023年第11期586-604,共19页软件工程与应用（英文）

摘　　要：This research paper explores the use of Generative Adversarial Networks (GANs) to synthetically generate insider threat scenarios. Insider threats pose significant risks to IT infrastructures, requiring effective detection and mitigation strategies. By training GAN models on historical insider threat data, synthetic scenarios resembling real-world incidents can be generated, including various tactics and procedures employed by insiders. The paper discusses the benefits, challenges, and ethical considerations associated with using GAN-generated data. The findings highlight the potential of GANs in enhancing insider threat detection and response capabilities, empowering organizations to fortify their defenses and proactively mitigate risks posed by internal actors.This research paper explores the use of Generative Adversarial Networks (GANs) to synthetically generate insider threat scenarios. Insider threats pose significant risks to IT infrastructures, requiring effective detection and mitigation strategies. By training GAN models on historical insider threat data, synthetic scenarios resembling real-world incidents can be generated, including various tactics and procedures employed by insiders. The paper discusses the benefits, challenges, and ethical considerations associated with using GAN-generated data. The findings highlight the potential of GANs in enhancing insider threat detection and response capabilities, empowering organizations to fortify their defenses and proactively mitigate risks posed by internal actors.

关 键 词：GANs CERT Insider-Threat CYBERSECURITY 

分 类 号：TN3[电子电信—物理电子学]