Secure edge computing : applications, techniques and challenges.

Format:

Book

Contributor:

Ahmed, Mohiuddin (Computer scientist), editor.

Dowland, Paul, editor.

Language:

English

Subjects (All):

Edge computing.

Computer security--Standards.

Computer security.

Physical Description:

1 online resource (305 pages)

Edition:

1st ed.

Place of Publication:

[S.l.] : CRC Press, 2021.

Summary:

The internet is making our daily life as digital as possible and this new era is called the Internet of Everything (IoE). Edge computing is an emerging data analytics concept that addresses the challenges associated with IoE. More specifically, edge computing facilitates data analysis at the edge of the network instead of interacting with cloud-based servers. Therefore, more and more devices need to be added in remote locations without any substantial monitoring strategy. Thisincreased connectivity and the devices used for edge computing will create more room for cyber criminals to exploit the system's vulnerabilities. Ensuring cyber security at the edge should not be an afterthought or a huge challenge. The devices used for edge computing are not designed with traditional IT hardware protocols. There are diverse-use cases in the context of edge computing and Internet of Things (IoT) in remote locations. However, the cyber security configuration and software updates are often overlooked whenthey aremost needed to fight cyber crime and ensure data privacy. Therefore, the threat landscape in the context of edge computing becomes wider and far more challenging. There is a clear needfor collaborative work throughout the entire value chain of the network. In this context, this bookaddresses the cyber security challenges associated with edge computing, whichprovides a bigger pictureof the concepts, techniques, applications, and open research directions in this area. In addition, the bookserves as a single source of reference for acquiring the knowledge on the technology, process and people involved in next generation computing and security. It will be a valuable aid for researchers, higher level students and professionals working in the area.

Contents:

Cover

Half Title

Title Page

Copyright Page

Dedication

Table of Contents

Preface

Acknowledgments

Editors

Contributors

Section I

Chapter 1: Secure Fog-Cloud of Things: Architectures, Opportunities and Challenges

1.1 Introduction

1.1.1 Chapter Road Map

1.2 Secure Fog-Cloud of Things

1.2.1 Environment

1.2.2 Architecture

1.3 Threats, Vulnerabilities and Exploits in Fog-Cloud of Things Ecosystems

1.4 Key Machine Learning Kits for Secure Fog-Cloud of Things Architecture

1.5 Applications

1.6 Opportunities and Challenges in Improving Security in Fog-Cloud of Things

1.6.1 Opportunities

1.6.2 Challenges

1.7 Future Trends

1.8 Conclusion

References

Chapter 2: Collaborative and Integrated Edge Security Architecture

2.1 Background

2.2 Edge Security Challenges

2.3 Perspectives of Edge Security Architecture

2.4 Emerging Trends and Enablers for Edge Security Architecture

2.4.1 The Edge Computing Architecture

2.4.2 Leveraging Fog-Based Security Architecture for Edge Networks

2.5 Collaborative and Integrated Security Architecture for Edge Computing

2.5.1 Overview

2.5.2 Distributed Virtual Firewall (DFWs)

2.5.3 Distributed Intrusion Detection Systems (IDSs)

2.6 Conclusion and Future Research

Chapter 3: A Systemic IoT-Fog-Cloud Architecture for Big-Data Analytics and Cyber Security Systems: A Review of Fog Computing

3.1 Introduction

3.2 Fog Computing Systems

3.2.1 Description of Fog

3.2.2 Characteristics of Fog

3.2.3 Systemic Architecture of IoT-Fog-Cloud

3.2.4 Applications of IoT, Fog and Cloud Systems

3.3 Cyber Security Challenges

3.4 Security Solutions and Future Directions

3.5 Conclusion

Chapter 4: Security and Organizational Strategy: A Cloud and Edge Computing Perspective

4.1 Introduction.

4.2 Cloud Computing and Cloud-based Computing

4.3 Business Operations and Management

4.3.1 Business Process

4.3.2 Business Continuity

4.3.3 Risk Management and Disaster Recovery

4.4 Human and Technological Factors

4.4.1 Human Factors

4.4.2 Technological Factors

4.4.3 Copyright and SLAs

4.5 Trust

4.5.1 Intra-organizational Trust

4.5.2 Inter-organizational Trust

4.6 Geographic Location

4.6.1 Regulations and Jurisdictions

4.6.2 Compliance and Governance

4.7 Conclusions

Chapter 5: An Overview of Cognitive Internet of Things: Cloud and Fog Computing

5.1 Introduction

5.2 Background of Fog, Cloud and Edge Computing

5.2.1 Fog Computing

5.2.1.1 Benefits of Fog Computing

5.2.1.2 Disadvantages of Fog Computing

5.2.2 Cloud Computing

5.2.2.1 Benefits of Cloud Computing

5.2.2.2 Disadvantages of Cloud Computing

5.2.3 Edge Computing

5.2.3.1 Benefits of Edge Computing

5.2.3.2 Disadvantages of Edge Computing

5.3 Literature Review of Existing Works

5.3.1 Review of Fog Computing

5.3.2 Review of Cloud Computing

5.3.3 Review of Edge Computing

5.4 Network Architecture

5.4.1 Computation Between Fog and Cloud

5.4.2 Computation Between Fog and Fog

5.5 Numerical Results

5.6 Conclusion

Chapter 6: Privacy of Edge Computing and IoT

6.1 Introduction

6.2 IoT Ecosystem

6.3 Privacy Spaces

6.4 The Technology of Privacy Spaces

6.4.1 Apple HomeKit

6.4.2 Google Home

6.5 Privacy Space Data Flows

6.6 Remote Access

6.7 Personal Data Store

6.8 Privacy-Preserving Techniques

6.8.1 Anonymization

6.8.2 k-Anonymization

6.8.3 Unicity

6.8.4 Differential Privacy

6.8.5 Privacy-Preserving Data Queries

6.9 Case Study: Contact Tracking Mobile Applications

6.10 Conclusions

Notes

Section II.

Chapter 7: Reducing the Attack Surface of Edge Computing IoT Networks via Hybrid Routing Using Dedicated Nodes

7.1 Introduction

7.2 Related Works

7.3 The Solution

7.3.1 Inference System of Trusted Time Server

7.3.2 Security Features

7.3.3 Synchronization with a Trusted Time Server

7.3.4 Transit Addresses

7.4 Test Methodology and Environment

7.4.1 TTS Server and Data Collection for Inference

7.4.2 Heterogeneous Network Environment

Simulation Case 1:

Simulation Case 2:

7.4.3 Graph-based Representation

7.5 Case Study

7.6 Conclusion

Chapter 8: Early Identification of Mental Health Disorder Employing Machine Learning-based Secure Edge Analytics: A Real-time Monitoring System

8.1 Introduction

8.2 Traditional Methods Implemented in Edge Computing

8.3 Secure Analytics of Smart Healthcare at the Edge

8.4 Related Work: Overview of Mobile Applications for Mental Health

8.4.1 Anxiety Reliever

8.4.2 Anxiety Coach

8.4.3 Breath2Relax

8.4.4 Happify

8.4.5 Head Space

8.4.6 Mindshift

8.4.7 MoodKit

8.4.8 Panic Relief

8.4.9 PTSD Coach

8.5 Methodologies for Automated Real-Time Mood Detection for Assessing Anxiety and Depression Levels in the Edge with Privacy-Preservation Capability

8.5.1 Data Preparation and Pre-processing

Face-tracking

8.5.1.1 Identifying Optic Flow in Facial Regions

8.5.2 Pre-processing and Noise Elimination of the Image Data

8.5.3 Questionnaire Data Description

8.5.4 Proposed Architecture

8.5.5 Data Analysis Using AI Techniques

8.5.6 Privacy Preservation of the Model

8.5.6.1 Federated Learning

8.5.7 Model Deployment on Edge Devices

8.6 Experimental Results

8.6.1 SqlLite Analysis

8.6.2 Machine Learning Algorithm Analysis

8.6.3 Federated Learning Analysis

8.6.4 Comparative Analysis.

8.7 Conclusion

Chapter 9: Harnessing Artificial Intelligence for Secure ECG Analytics at the Edge for Cardiac Arrhythmia Classification

9.1 Introduction

9.2 Literature Review

9.3 Dataset Preparation

9.4 Methodology

9.4.1 ECG Pre-processing Phase

9.4.2 Heartbeat Segmentation Phase

9.4.3 Feature Extraction Phase

9.4.4 Learning/Classification Phase

9.5 Experimental Setups, Results and Discussion

9.5.1 Performance Indicators

9.5.2 Results for Experimental Setup 1

9.5.3 Results for Experimental Setup 2

9.6 Conclusion

Chapter 10: On Securing Electronic Healthcare Records Using Hyperledger Fabric Across the Network Edge

10.1 Introduction

10.2 Existing Decentralized Security Methods: Can Blockchain Be Used At the Edge?

10.2.1 Current EHR System in Canada

10.2.2 Challenges with the Traditional EHR Systems

10.2.3 Security Measures for Health Records

10.3 Current Challenges Faced by the Healthcare Workers in Covid-19 Pandemic

10.3.1 Importance and Role of Medical Records During Pandemic

10.3.2 Challenges Faced by Doctors

10.3.3 Understanding the Proposed Architecture Using COVID-19 Example

10.4 Scalable Secure Management and Access Control of Electronic Health Records at the Edge

10.4.1 The Importance of Integrating Blockchain and Edge Computing?

10.4.2 Challenges

10.5 Overview of Blockchain and Hyper Ledger Methodologies

10.5.1 Blockchain

10.5.2 Electronic Health Records (EHRs)

10.5.3 Smart Contract

10.5.4 Access Control in Medical Domain

10.5.5 Hyperledger

10.5.6 Composer Tools

10.5.7 Playground

10.5.8 Off-chain Storage

10.5.9 User Experience From Patient's Side

10.6 Hyper Ledger-Based Proposed Architecture for Protecting Electronic Health Records

10.6.1 Proposed Architecture of the Blockchain System.

10.6.2 Data Flow Diagrams

10.6.2.1 Doctors

10.6.2.2 Patient

10.6.2.3 Transaction Flow

10.7 Performance Evaluation

10.7.1 Performance of the Proposed Model

10.7.2 Performance Comparison

10.8 Conclusions and Future Caveats

Chapter 11: AI-Aided Secured ECG Live Edge Monitoring System with a Practical Use-Case

11.1 Introduction

11.1.1 Background

11.1.2 Problem Statement

11.1.3 Objective and Scope

11.2 Related Work

11.3 Proposed AI-Based System Architecture

11.3.1 Block Diagram

11.3.2 Data Collection and Pre-Processing Steps

11.3.3 Detecting Heart Abnormalities Using AI-Aided Techniques

11.4 Considered Smart ECG Monitoring System

11.4.1 Edge Hardware Components

11.4.1.1 System-on-a-Chip (SoC) Model

11.4.1.2 IoT Sensor for Heart Rate Data Acquisition

11.4.1.3 Microprocessor and Analog to Digital Converter

11.4.2 AI-Logic Component

11.4.2.1 Decision Tree

11.4.2.2 Random Forest

11.4.2.3 ANN

11.4.2.4 CNN

11.5 Bio-Authentication Application of the Considered ECG Monitoring System for Specific Use-Cases

11.6 Performance Evaluation

11.6.1 Supraventricular Arrhythmia Classification

11.6.2 Authorized User Classification for Bio-Authentication System

11.7 Challenges Involved with the Proposed System

Limitations

11.8 Conclusion and Future Scope

Section III

Chapter 12: Application of Unmanned Aerial Vehicles in Wireless Networks: Mobile Edge Computing and Caching

12.1 Introduction

12.1.1 Chapter Roadmap

12.2 Literature Review

12.3 Description of Caching and Mobile Edge Computing

12.3.1 Overview of Caching

12.3.1.1 Advantages

12.3.1.2 Disadvantages

12.3.2 Overview of Mobile Edge Computing

12.3.2.1 Advantages

12.3.2.2 Disadvantages

12.4 Layering of UAV-Based MEC Architecture.

12.4.1 Explanation of the Layers.

Notes:

Description based on print version record.

ISBN:

1-00-302863-2

1-000-42731-5

1-003-02863-2

1-000-42732-3

9781003028635

OCLC:

1259323273

Publisher Number:

10.1201/9781003028635