articleIEEE Internet of Things JournalOct 3, 2022HYBRID OA

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

CPCheol-Hee ParkJLJonghoon LeeYKYoungsoo KimJPJong‐Geun ParkHKHyunjin Kim

Electronics and Telecommunications Research Institute · Kongju National University

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Abstract

As communication technology advances, various and heterogeneous data are communicated in distributed environments through network systems. Meanwhile, along with the development of communication technology, the attack surface has expanded, and concerns regarding network security have increased. Accordingly, to deal with potential threats, research on network intrusion detection systems (NIDSs) has been actively conducted. Among the various NIDS technologies, recent interest is focused on artificial intelligence (AI)-based anomaly detection systems, and various models have been proposed to improve the performance of NIDS. However, there still exists the problem of data imbalance, in which AI models cannot…

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Topics
Keywords
  • Computer science
  • Autoencoder
  • Intrusion detection system
  • Artificial intelligence
  • Adversarial system
  • Machine learning
  • Anomaly detection
  • Artificial neural network
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