MirageNet - Towards a GAN-based Framework for Synthetic Network Traffic Generation

Author:

Nukavarapu Santosh Kumar1,Ayyat Mohammed1,Nadeem Tamer1

Affiliation:

1. Virginia Commonwealth University,Department of Computer Science,Richmond,VA,USA,23220

Funder

US National Science Foundation

Publisher

IEEE

Reference23 articles.

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Synthetic and privacy-preserving traffic trace generation using generative AI models for training Network Intrusion Detection Systems;Journal of Network and Computer Applications;2024-09

2. Autonomous On-Device Protocols: Empowering Wireless with Self-Driven Capabilities;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

3. NetDiffusion: Network Data Augmentation Through Protocol-Constrained Traffic Generation;Proceedings of the ACM on Measurement and Analysis of Computing Systems;2024-02-16

4. Optimizing Honeypot Placement Strategies with Graph Neural Networks for Enhanced Resilience via Cyber Deception;Proceedings of the 2nd on Graph Neural Networking Workshop 2023;2023-12-05

5. Class-Aware Neural Networks for Efficient Intrusion Detection on Edge Devices;2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON);2023-09-11

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