Generative Adversarial Networks-Driven Cyber Threat Intelligence Detection Framework for Securing Internet of Things

Mohamed Amine Ferrag, Djallel Hamouda, Merouane Debbah, Leandros Maglaras, Abderrahmane Lakas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

While the benefits of 6G-enabled Internet of Things (IoT) are numerous, providing high-speed, low-latency communication that brings new opportunities for innovation and forms the foundation for continued growth in the IoT industry, it is also important to consider the security challenges and risks associated with the technology. In this paper, we propose a two-stage intrusion detection framework for securing IoTs, which is based on two detectors. In the first stage, we propose an adversarial training approach using generative adversarial networks (GAN) to help the first detector train on robust features by supplying it with adversarial examples as validation sets. Consequently, the classifier would perform very well against adversarial attacks. Then, we propose a deep learning (DL) model for the second detector to identify intrusions. We evaluated the proposed approach's efficiency in terms of detection accuracy and robustness against adversarial attacks. Experiment results with a new cyber security dataset demonstrate the effectiveness of the proposed methodology in detecting both intrusions and persistent adversarial examples with a weighted avg of 96%, 95%, 95 %, and 95% for precision, recall, f-score, and accuracy, respectively.

Original languageEnglish
Title of host publicationProceedings - 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages196-200
Number of pages5
ISBN (Electronic)9798350346497
DOIs
Publication statusPublished - 2023
Event19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023 - Pafos, Cyprus
Duration: Jun 19 2023Jun 21 2023

Publication series

NameProceedings - 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

Conference

Conference19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023
Country/TerritoryCyprus
CityPafos
Period6/19/236/21/23

Keywords

  • Adversarial attacks
  • Adversarial deep learning
  • GAN
  • Generative AI
  • IoT

ASJC Scopus subject areas

  • Instrumentation
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

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