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A lightweight IoT intrusion detection model based on improved BERT-of-Theseus

  • Published:2024-03 Issue: Volume:238 Page:122045
  • ISSN:0957-4174
  • Container-title:Expert Systems with Applications
  • language:en
  • Short-container-title:Expert Systems with Applications

Author:

Wang Zhendong,Li Jingfei,Yang Shuxin,Luo Xiao,Li Dahai,Mahmoodi Soroosh

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangxi Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference64 articles.

1. A survey of machine and deep learning methods for internet of things (IoT) security;Al-Garadi;IEEE Communications Surveys & Tutorials,2020

2. TON_IoT telemetry dataset: A new generation dataset of IoT and IIoT for data-driven intrusion detection systems;Alsaedi;IEEE Access,2020

3. Detecting IoT botnets based on the combination of cooperative game theory with deep and machine learning approaches;Asadi;Journal of Ambient Intelligence and Humanized Computing,2022

4. IoTBoT-IDS: A novel statistical learning-enabled botnet detection framework for protecting networks of smart cities;Ashraf;Sustainable Cities and Society,2021

5. Ba, J. L., Kiros, J. R., & Hinton, G. E. (2016). Layer normalization. arXiv preprint arXiv:1607.06450.

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