An Enhanced AI-Based Network Intrusion Detection System Using Generative Adversarial Networks-Reference-Cited by-同舟云学术

An Enhanced AI-Based Network Intrusion Detection System Using Generative Adversarial Networks

Published:2023-02-01 Issue:3 Volume:10 Page:2330-2345
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Park Cheolhee¹^ORCID,Lee Jonghoon¹^ORCID,Kim Youngsoo¹,Park Jong-Geun¹^ORCID,Kim Hyunjin¹,Hong Dowon²^ORCID

Affiliation:

1. Cyber Security Research Division, Electronics and Telecommunications Research Institute, Daejeon, South Korea

2. Department of Applied Mathematics, Kongju National University, Gongju, South Korea

Funder

Institute of Information and Communications Technology Planning and Evaluation

Korea Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10024910/09908159.pdf?arnumber=9908159

Reference43 articles.

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4. Improving Attack Detection Performance in NIDS Using GAN

5. Addressing Imbalanced Data Problem with Generative Adversarial Network For Intrusion Detection

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