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Big Data Analytics in Fog-Enabled IoT Networks

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advanced IoT network security solutions
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Age Group_Uncategorized
artificial intelligence security
AUC Roc
automatic-update
B01=Brij B. Gupta
B01=Govind P. Gupta
B01=Kwok Tai Chui
B01=Rakesh Tripathi
big data analytics
Binary Dataset
blockchain
Category1=Non-Fiction
Category=UK
Category=UKL
Category=UT
Category=UTN
Category=UY
Cloud Data Centres
COP=United Kingdom
CTI
Cyber threat detection
cybersecurity analytics
Delivery_Pre-order
Dl Model
Dl Technique
Edge Computing
Edge Nodes
energy management optimization
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
F1 Score
Feature Selection
federated learning methods
Fog Computing
Fog-enabled IoT Networks
GBDT
Gradient Boosting
healthcare data privacy
Honey Bee
intrusion detection systems
IoT Application
IoT Big Data
IoT Device
IoT Network
IoT System
Language_English
Latent Dirichlet Allocation
Make Span
Malware Detection
PA=Not yet available
Price_€50 to €100
PS=Forthcoming
Random Forest
smart grid applications
softlaunch
Standard PSO
VM

Product details

  • ISBN 9781032206455
  • Weight: 360g
  • Dimensions: 156 x 234mm
  • Publication Date: 08 Oct 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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Description

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.