Affiliation:
1. Institute of Telecommunications, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krakow, Poland
Abstract
Wireless Local Area Networks (WLANs) have revolutionized modern communication by providing a user-friendly and cost-efficient solution for Internet access and network resources. However, the increasing popularity of WLANs has also led to a rise in security threats, including jamming, flooding attacks, unfair radio channel access, user disconnection from access points, and injection attacks, among others. In this paper, we propose a machine learning algorithm to detect Layer 2 threats in WLANs through network traffic analysis. Our approach uses a deep neural network to identify malicious activity patterns. We detail the dataset used, including data preparation steps, such as preprocessing and division. We demonstrate the effectiveness of our solution through series of experiments and show that it outperforms other methods in terms of precision. The proposed algorithm can be successfully applied in Wireless Intrusion Detection Systems (WIDS) to enhance the security of WLANs and protect against potential attacks.
Funder
National Research Institute
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference48 articles.
1. (2021). IEEE Standard for Information Technology–Telecommunications and Information Exchange between Systems-Local and Metropolitan Area Networks–Specific Requirements-Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. Standard No. 802.11-2020.
2. (2021). IEEE Standard for Information Technology–Telecommunications and Information Exchange between Systems–Local and Metropolitan Area Networks-Specific Requirements–Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications-Amendment 3: Wake-Up Radio Operation. Standard No. IEEE Std 802.11ba-2021 (Amendment to IEEE Std 802.11-2020 as Amendment by IEEE Std 802.11ax-2021, and IEEE Std 802.11ay-2021).
3. Natkaniec, M., and Bieryt, N. (2023). An Analysis of the Mixed IEEE 802.11ax Wireless Networks in the 5 GHz Band. Sensors, 23.
4. Information Security of PHY Layer in Wireless Networks;Fang;J. Sensors,2016
5. Vanhoef, M., and Piessens, F. (2014, January 8–12). Advanced Wi-Fi attacks using commodity hardware. Proceedings of the 30th Annual Computer Security Applications Conference, New Orleans, LA, USA.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献