Deep Representation Learning for Cyber-Attack Detection in Industrial IoT-Reference-Cited by-同舟云学术

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Deep Representation Learning for Cyber-Attack Detection in Industrial IoT

Published:2021 Issue: Volume: Page:139-162
ISSN:
Container-title:AI-Enabled Threat Detection and Security Analysis for Industrial IoT
language:
Short-container-title:

Author:

Jahromi Amir Namavar,Karimipour Hadis,Dehghantanha Ali,Parizi Reza M.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-76613-9_8

Reference73 articles.

1. HaddadPajouh H, Dehghantanha A, M. Parizi R, et al (2019) A survey on internet of things security: Requirements, challenges, and solutions. Internet of Things 100129. https://doi.org/10.1016/j.iot.2019.100129

2. Sakhnini J, Karimipour H, Dehghantanha A, et al (2019) Security aspects of Internet of Things aided smart grids: A bibliometric survey. Internet of Things 100111. https://doi.org/10.1016/j.iot.2019.100111

3. SonicWall (2020) 2020 SonicWall cyber threat report

4. Singh S, Karimipour H, HaddadPajouh H, Dehghantanha A (2020) Artificial Intelligence and Security of Industrial Control Systems. In: Choo K-KR, Dehghantanha A (eds) Handbook of Big Data Privacy. Springer International Publishing, Cham, pp 121–164

5. Karimipour H, Dehghantanha A, Parizi RM, et al (2019) A Deep and Scalable Unsupervised Machine Learning System for Cyber-Attack Detection in Large-Scale Smart Grids. IEEE Access 7:80778–80788. https://doi.org/10.1109/ACCESS.2019.2920326

Cited by 1 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

1. Introduction to Cyber-Physical Security and Resilience;Security and Resilience in Cyber-Physical Systems;2022

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