Security and Risk Analysis for Intelligent Edge Computing

ISBN-13: 9783031281495 / Angielski

Gautam Srivastava; Uttam Ghosh; Jerry Chun-Wei Lin

Opis

This book offers the latest research results in security and privacy for Intelligent Edge Computing Systems. It presents state-of-the art content and provides an in-depth overview of the basic background in this related field. Practical areas in both security and risk analysis are addressed as well as connections directly linked to Edge Computing paradigms. This book also offers an excellent foundation on the fundamental concepts and principles of security, privacy and risk analysis in Edge Computation infrastructures. It guides the reader through the core ideas with relevant ease.Edge Computing has burst onto the computational scene offering key technologies for allowing more flexibility at the edge of networks. As Edge Computing has evolved as well as the need for more in-depth solutions in security, privacy and risk analysis at the edge. This book includes various case studies and applications on Edge Computing. It includes the Internet of Things related areas, such as smart cities, blockchain, mobile networks, federated learning, cryptography and cybersecurity.This book is one of the first reference books covering security and risk analysis in Edge Computing Systems. Researchers and advanced-level students studying or working in Edge Computing and related security fields will find this book useful as a reference. Decision makers, managers and professionals working within these fields will want to purchase this book as well.
 

Spis treści

Chap I Introduction to Cloud/Edge Computing  

Chap II Big Data Analytics and Security over the Cloud: Characteristics, Analytics, Integration and Security

Chap III Federated Learning enabled Edge computing

security for Internet of Medical Things: Concepts, Challenges and Open issues

Chap IV Embedded Edge and Cloud Intelligence

Chap V The Analysis on Impact of Cyber Security Threats on Smart Grids

Chap VI Intelligent Intrusion Detection algorithm based on multi-attack for Edge-Assisted Internet of Things

Chap VII Secure Data Analysis and Data Privacy

Chap VIII A Novel Trust evaluation and Reputation data Management based Security System Model for Mobile Edge Computing Network

Chap IX Network Security System in Mobile Edge Computing-to-IoMT Networks using Distributed Approach

Chap X Wireless and Mobile Security in Edge Computing

Chap XI An intelligent facial expression recognizer using modified 1 ResNet-110 using Edge Computing

Chap XII Blockchain Based Simulated Virtual Machine Placement Hybrid Approach for Decentralized cloud and edge computing environment and Edge Computing

 

O autorze

Dr. Gautam Srivastava (Senior Member, IEEE) is at Brandon University in Brandon, Manitoba, Canada, where he currently is an Associate Professor. During his 10-year academic career, he has published a total of 400 papers in high-impact conferences and journals. His research program is federally funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) and MITACS.

 

Dr. Uttam Ghosh is working as Associate Professor of Cybersecurity at the Department of Computer Science and Data Science, Meharry Medical College, TN, USA. He obtained his MS and PhD in Electronics and Electrical Communication Engineering from the Indian Institute of Technology (IIT) Kharagpur, India in 2009 and 2013 respectively. Dr. Ghosh has post-doctoral experiences at the University of Illinois in Urbana-Champaign, Fordham University, and Tennessee State University. Recently, he has received research funding from the US National Science Foundation (NSF) on edge-cloud interplay for intelligent healthcare.

 

Dr. Jerry Chun-Wei Lin is currently working as the full Professor at the Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway. He has published 500+ research papers in refereed journals 85+ IEEE/ACM journals) and international conferences. His research interests include data mining and analytics, soft computing, deep learning/machine learning, optimization, IoT applications, privacy-preserving and security technologies, and bio-informatics.