Deep Learning for Security and Privacy Preservation in IoT
This book addresses the issues with privacy and security in Internet of things (IoT) networks which are susceptible to cyber-attacks and proposes deep learning-based approaches using artificial neural networks models to achieve a safer and more secured IoT environment. Due to the inadequacy of exist...
| Other Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Singapore
Springer Nature Singapore
2021, 2021
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| Edition: | 1st ed. 2021 |
| Series: | Signals and Communication Technology
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Metamorphosis of Industrial IoT using Deep Leaning
- Deep Learning Models and their Architectures for Computer Vision Applications: A Review
- IoT Data Security with Machine Learning Blockchain: Risks and Countermeasures
- A Review on Cyber Crimes on the Internet of Things
- Deep learning framework for anomaly detection in IoT enabled systems
- Anomaly Detection using Unsupervised Machine Learning Algorithms
- Game Theory Based Privacy Preserving Approach for Collaborative Deep Learning in IoT
- Deep Learning based security preservation of IoT: An industrial machine health monitoring scenario
- Deep learning Models: An Understandable Interpretable Approaches