Detecting the undetectable: GAN-based strategies for network intrusion detection
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s41870-024-02172-7.pdf
Reference18 articles.
1. Dunmore A, Jang-Jaccard J, Sabrina F, Kwak J (2023) A comprehensive survey of generative adversarial networks (GANs) in cybersecurity intrusion detection. IEEE Access 11:76071–76094. https://doi.org/10.1109/ACCESS.2023.3296707
2. Arora A, Shantanu A (2020) A review on application of GANs in cybersecurity domain. IETE Tech Rev 39(2):433–441. https://doi.org/10.1080/02564602.2020.1854058
3. Dutta IK, Ghosh B, Carlson A, Totaro M, Bayoumi M (2020) Generative adversarial networks in security: a survey. In: Proceedings of the 11th IEEE annual ubiquitous computing, electronics & mobile communication conference (UEMCON), pp 399–405
4. Cai Z, Xiong Z, Xu H, Wang P, Li W, Pan Y (2021) Generative adversarial networks: a survey toward private and secure applications. ACM Comput Surv 54(6):1–38. https://doi.org/10.1145/3459992
5. Chhetri SR, Lopez AB, Wan J, Al Faruque MA (2019) Gan-sec: generative adversarial network modeling for the security analysis of cyber-physical production systems. In: 2019 design automation test in Europe conference exhibition (DATE), pp 770–775. https://doi.org/10.23919/DATE.2019.8715283
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