Deep Learning for Security and Privacy Preservation in IoT
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Beschreibung
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 existing solutions to cover the entire IoT network security spectrum, the book utilizes artificial neural network models, which are used to classify, recognize, and model complex data including images, voice, and text, to enhance the level of security and privacy of IoT. This is applied to several IoT applications which include wireless sensor networks (WSN), meter reading transmission in smart grid, vehicular ad hoc networks (VANET), industrial IoT and connected networks. The book serves as a reference for researchers, academics, and network engineers who want to develop enhanced security and privacy features in the design of IoT systems.
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 existing solutions to cover the entire IoT network security spectrum, the book utilizes artificial neural network models, which are used to classify, recognize, and model complex data including images, voice, and text, to enhance the level of security and privacy of IoT. This is applied to several IoT applications which include wireless sensor networks (WSN), meter reading transmission in smart grid, vehicular ad hoc networks (VANET), industrial IoT and connected networks. The book serves as a reference for researchers, academics, and network engineers who want to develop enhanced security and privacy features in the design of IoT systems.
Addresses the issues with privacy and security in Internet of Things (IoT) networks Proposes deep learning-based approaches using artificial neural networks models to enhance IoT data security Demonstrates the application of the security models in several IoT systems
Autor*in
Aaisha Makkar
Themen in »Deep Learning for Security and Privacy Preservation in IoT«
Deep Learning Internet of Things (IoT) Network Security Vehicular Ad hoc Networks (VANETs) Wireless Sensors Network Mobile Ad hoc Networks (MANETs) Machine Learning Artificial Neural Networks Secure Data Aggregation Privacy-Preserving Meter