Big Data Analytics in Fog-Enabled IoT Networks

图书简介

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.

1. Deep Learning Techniques in Big Data Enabled Internet-of-Things Devices by Sourav Singh, Sachin Sharma, Shuchi Bhadula. 2. IoMT based Smart Health Monitoring: The Future of HealthCare by Indrashis Mitra, Yashi Srivastava, Kananbala Ray, Tejaswini Kar. 3. A Review on Intrusion Detection System and Cyber Threat Intelligence for Secure IoT-enabled Network: Challenges and Directions by Prabhat Kumar, Govind P. Gupta and Rakesh Tripathi. 4. Self-adaptive application monitoring for decentralized Edge frameworks by Monika Saxena, Kirti Pandey, Vaibhav Vyas, C.K. Jha. 5. Federated Learning and its Application in Malware Detection by Sakshi Bhagwat, Govind P. Gupta. 6. An Ensemble XGBoost Approach for the Detection of Cyberattacks in the Industrial IOT Domain by R.K. Pareriya, Priyanka Verma, Pathan Suhana. 7. A review on IoT for the application of energy, environment, and waste management: system architecture and future direction by C. Rakesh, T. Vivek, K. Balaji. 8. Analysis of Feature Selection Methods for Android Malware Detection using Machine Learning Techniques by Santosh K. Smmarwar, Govind P. Gupta, Sanjay Kumar. 9. An Efficient Optimizing Energy Consumption using Modified Bee Colony Optimization in Fog and IoT Networks by Potu Narayana, Chandrashekar Jatoth, Premchand Paravataneni, G Rekha.

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Big Data Analytics in Fog-Enabled IoT Networks 支持雾的物联网网络中的大数据分析：朝向隐私和安全的角度 计算机应用

Big Data Analytics in Fog-Enabled IoT Networks

支持雾的物联网网络中的大数据分析：朝向隐私和安全的角度
计算机应用