AI-Enabled Threat Detection and Security Analysis for Industrial IoT

AI-Enabled Threat Detection and Security Analysis for Industrial IoT

Karimipour, Hadis; Derakhshan, Farnaz

Springer Nature Switzerland AG

08/2022

250

Mole

Inglês

9783030766153

15 a 20 dias

403

Descrição não disponível.
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.
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Internet of Things;Industry 4.0;Industrial Internet of Things;cyber-physical system;cybersecurity;threat intelligence;machine learning;intrusion detection;anomaly detection;attack identification;attack prevention;artificial intelligent;deep learning;smart grid