Big Data Analytics in Fog Enabled IoT Networks Towards a Privacy and Security Perspective 1st Edition Kwok Tai Gupta, Govind, Tripathi, Rakesh, Gupta, Brij, Chui ISBN 1000861864 9781000861860

Big Data Analytics in Fog Enabled IoT Networks Towards a Privacy and Security Perspective 1st Edition Kwok Tai Gupta, Govind, Tripathi, Rakesh, Gupta, Brij, Chui – Ebook PDF Instant Download/Delivery: 1000861864, 9781000861860
Full dowload Big Data Analytics in Fog Enabled IoT Networks Towards a Privacy and Security Perspective 1st Edition after payment

Product details:

 
ISBN 10: 1000861864
ISBN 13: 9781000861860
Author: Kwok Tai Gupta, Govind P., Tripathi, Rakesh, Gupta, Brij B.,Chui 

The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks. This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system.

Table of contents:

Chapter 1 Deep Learning Techniques in Big Data-Enabled Internet-of-Things Devices

Chapter 2 IoMT-based Smart Health Monitoring: The Future of Health Care

Chapter 3 A Review on Intrusion Detection Systems and Cyber Threat Intelligence for Secure IoT-enabled Networks: Challenges and Directions

Chapter 4 Self-adaptive Application Monitoring for Decentralized Edge Frameworks

Chapter 5 Federated Learning and its Application in Malware Detection

Chapter 6 An Ensemble XGBoost Approach for the Detection of Cyber-attacks in the Industrial IoT Domain

Chapter 7 A Review on IoT for the Application of Energy, Environment, and Waste Management: System Architecture and Future Directions

Chapter 8 Analysis of Feature Selection Methods for Android Malware Detection using Machine Learning Techniques

Chapter 9 An Efficient Optimizing Energy Consumption using Modified Bee Colony Optimization in Fog and IoT Networks

Index

People also search:

    
iot fog
    
fog in iot
    
fog data science
    
iot big data analytics
    
fog networking