ProGen: Projection-Based Adversarial Attack Generation Against Network Intrusion Detection-Reference-Cited by-同舟云学术

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ProGen: Projection-Based Adversarial Attack Generation Against Network Intrusion Detection

Published:2024 Issue: Volume:19 Page:5476-5491
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Wang Minxiao¹,Yang Ning²^ORCID,Forcade-Perkins Nicolas J.³,Weng Ning¹^ORCID

Affiliation:

1. Computer Engineering Program, School of Electrical, Computer, and Biomedical Engineering, Southern Illinois University, Carbondale, IL, USA

2. Information Technology Program, School of Computing, Southern Illinois University, Carbondale, IL, USA

3. School of Electrical, Computer, and Biomedical Engineering, Southern Illinois University, Carbondale, IL, USA

Funder

Dr. Yang’s Startup Fund

NSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/10206/10319981/10531273.pdf?arnumber=10531273

Reference38 articles.

1. Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems

2. The Role of Machine Learning in Cybersecurity

3. Wasserstein generative adversarial networks;Arjovsky

4. SynGAN: Towards generating synthetic network attacks using GANs;Charlier;arXiv:1908.09899,2019

5. FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments

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