Gradient scaling and segmented SoftMax Regression Federated Learning (GDS-SRFFL): a novel methodology for attack detection in industrial internet of things (IIoT) networks-Reference-Cited by-同舟云学术

Gradient scaling and segmented SoftMax Regression Federated Learning (GDS-SRFFL): a novel methodology for attack detection in industrial internet of things (IIoT) networks

Published:2024-04-17 Issue:12 Volume:80 Page:16860-16886
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Rajasekaran Vijay Anand,Indirajithu Alagiri,Jayalakshmi P.,Nayyar Anand,Balusamy Balamurugan

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11227-024-06109-6.pdf

Reference26 articles.

1. Altunay HC, Albayrak Z (2023) A hybrid CNN+ LSTM based intrusion detection system for industrial IoT networks. Eng Sci Technol Int J 38:101322. https://doi.org/10.1016/j.jestch.2022.101322

2. Khan F, Alturki R, Rahman MA, Mastorakis S, Razzak I, Shah ST (2022) Trustworthy and reliable deep-learning-based cyberattack detection in industrial IoT. IEEE Trans Ind Inf 19(1):1030–1038. https://doi.org/10.1109/TII.2022.3190352

3. Salehi M, De Borger G, Hughes D, Crispo B (2022) NemesisGuard: mitigating interrupt latency side channel attacks with static binary rewriting. Comput Netw 205:108744. https://doi.org/10.1016/j.comnet.2021.108744

4. Ngo QD, Nguyen HT, Le VH, Nguyen DH (2020) A survey of IoT malware and detection methods based on static features. ICT Express 6(4):280–286. https://doi.org/10.1016/j.icte.2020.04.005

5. Yazdinejad A, Kazemi M, Parizi RM, Dehghantanha A, Karimipour H (2023) An ensemble deep learning model for cyber threat hunting in industrial internet of things. Digit Commun Netw 9(1):101–110. https://doi.org/10.1016/j.dcan.2022.09.008