AI-Enabled Threat Detection and Security Analysis for Industrial IoT
This contributed volume provides the state-of-the-art development on security and privacy for cyber-physical systems (CPS) and industrial Internet of Things (IIoT). More specifically, this book discusses the security challenges in CPS and IIoT systems as well as how Artificial Intelligence (AI) and...
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| Other Authors: | , |
| Language: | English |
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Cham :
Springer International Publishing : Imprint: Springer,
2021.
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| Edition: | 1st ed. 2021. |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-030-76613-9 |
Table of Contents:
- Artificial Intelligence for Threat Detection and Analysis in Industrial IoT: Applications and Challenges
- Complementing IIoT Services through AI: Feasibility and Suitability
- Data Security and Privacy in Industrial IoT
- Blockchain Applications in the Industrial Internet of Things
- Application of Deep Learning on IoT-enabled Smart Grid Monitoring
- Cyber Security of Smart Manufacturing Execution Systems: A Bibliometric Analysis
- The Role of Machine Learning in IIoT Through FPGAs
- Deep Representation Learning for Cyber-Attack Detection in Industrial IoT
- Classification and Intelligent Mining of Anomalies in Industrial IoT
- A Snapshot Ensemble Deep Neural Network Model for Attack Detection in Industrial Internet of Things
- Privacy Preserving Federated Learning Solution for Security of Industrial Cyber Physical Systems
- A Multi-Stage Machine Learning Model for Security Analysis in Industrial Control System
- A Recurrent Attention Model for Cyber Attack Classification.