Wireless Intrusion Detection Using Shallow Neural Network Models

Ozturk S. B., AYDOS M.

2023 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2023, İstanbul, Turkey, 4 - 07 July 2023, pp.39-44 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/blackseacom58138.2023.10299700
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.39-44
  • Keywords: Cybersecurity, Shallow Neural Networks, Wireless Intrusion Detection System, Wireless Network Security
  • Hacettepe University Affiliated: Yes


Wireless systems, due to their nature lack the security features against various attacks such as jamming and eavesdropping. In order to successfully detect such attacks that occur in a wireless network, Artificial Intelligence (AI) models which continuously monitor wireless statistic records are used. On this context, this paper proposes an artificial neural networks based Wireless Intrusion Detection System (WIDS) for 802.11 (Wi-Fi) wireless networks, where the model is trained with public Aegean Wi-Fi Intrusion Dataset (AWID-2).