mlsanityData to 7 Oct 2026

A Survey on the Application of Generative Adversarial Networks in Cybersecurity: Prospective, Direction and Open Research Scopes

arXiv 2407.08839 ↗First posted 11 Jul 2024cs.CR cs.AI cs.CVcited by 2

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Abstract (arXiv)

With the proliferation of Artificial Intelligence, there has been a massive increase in the amount of data required to be accumulated and disseminated digitally. As the data are available online in digital landscapes with complex and sophisticated infrastructures, it is crucial to implement various defense mechanisms based on cybersecurity. Generative Adversarial Networks (GANs), which are deep learning models, have emerged as powerful solutions for addressing the constantly changing security issues. This survey studies the significance of the deep learning model, precisely on GANs, in strengthening cybersecurity defenses. Our survey aims to explore the various works completed in GANs, such as Intrusion Detection Systems (IDS), Mobile and Network Trespass, BotNet Detection, and Malware Detection. The focus is to examine how GANs can be influential tools to strengthen cybersecurity defenses in these domains. Further, the paper discusses the challenges and constraints of using GANs in these areas and suggests future research directions. Overall, the paper highlights the potential of GANs in enhancing cybersecurity measures and addresses the need for further exploration in this field.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 35 of its 106 references that are in the map. First posted on arXiv 11 Jul 2024.

Builds on

35 of 106 references.

References · 35

  1. 2016InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Netscited by 858
  2. 2023From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacycited by 137
  3. 2016Technical Report on the CleverHans v2.1.0 Adversarial Examples Librarycited by 123
  4. 2020OpenAttack: An Open-source Textual Adversarial Attack Toolkitcited by 84
  5. 2020DeepRobust: A PyTorch Library for Adversarial Attacks and Defensescited by 78
  6. 2017Generating Adversarial Malware Examples for Black-Box Attacks Based on GANcited by 74
  7. 2024Task-Agnostic Detector for Insertion-Based Backdoor Attackscited by 23
  8. 2021Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-Artcited by 18
  9. 2022Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervisioncited by 16
  10. 2022A Learnable Variational Model for Joint Multimodal MRI Reconstruction and Synthesiscited by 16
  11. 2023Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challengescited by 14
  12. 2021EvilModel 2.0: Bringing Neural Network Models into Malware Attackscited by 13
23 more
  1. 2024DeepGI: An Automated Approach for Gastrointestinal Tract Segmentation in MRI Scanscited by 13
  2. 2022Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagationcited by 12
  3. 2022TrafficFlowGAN: Physics-informed Flow based Generative Adversarial Network for Uncertainty Quantificationcited by 11
  4. 2020A Performance-Sensitive Malware Detection System Using Deep Learning on Mobile Devicescited by 9
  5. 2023Generative AI for Cyber Threat-Hunting in 6G-enabled IoT Networkscited by 9
  6. 2023Balanced Training for Sparse GANscited by 8
  7. 2024Comprehensive evaluation of Mal-API-2019 dataset by machine learning in malware detectioncited by 8
  8. 2020G-IDS: Generative Adversarial Networks Assisted Intrusion Detection Systemcited by 7
  9. 2022Quantifying Uncertainty In Traffic State Estimation Using Generative Adversarial Networkscited by 7
  10. 2023RIDE: Real-time Intrusion Detection via Explainable Machine Learning Implemented in a Memristor Hardware Architecturecited by 7
  11. 2024Mapping New Realities: Ground Truth Image Creation with Pix2Pix Image-to-Image Translationcited by 7
  12. 2020Multiscale Detection of Cancerous Tissue in High Resolution Slide Scanscited by 6
  13. 2020Deperturbation of Online Social Networks via Bayesian Label Transitioncited by 6
  14. 2020Perigee: Efficient Peer-to-Peer Network Design for Blockchainscited by 5
  15. 2020Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Networkscited by 5
  16. 2021Non-Exhaustive Learning Using Gaussian Mixture Generative Adversarial Networkscited by 4
  17. 2021EVAGAN: Evasion Generative Adversarial Network for Low Data Regimescited by 4
  18. 2023Robust Node Representation Learning via Graph Variational Diffusion Networkscited by 4
  19. 2020A Novel Learnable Gradient Descent Type Algorithm for Non-convex Non-smooth Inverse Problemscited by 2
  20. 2022FGAN: Federated Generative Adversarial Networks for Anomaly Detection in Network Trafficcited by 2
  21. 2018Malware detection techniques for mobile devicescited by 1
  22. 2019Extra Proximal-Gradient Inspired Non-local Networkcited by 1
  23. 2023Goldfish: Peer selection using Matrix completion in unstructured P2P networkcited by 1

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Citing papers per year: 2025: 2.

2 papers.

  1. 2025Adversarial Defense in Cybersecurity: A Systematic Review of GANs for Threat Detection and Mitigationcited by 1
  2. 2025Optimizing IoT Threat Detection with Kolmogorov-Arnold Networks (KANs)cited by 0