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Beschreibung

This reference reviews the architectural requirements of IT systems that are designed to digitally transform business operations. It is a compilation of 7 timely reviews that demonstrate how adopting emerging technologies and examining the security-based concerns can lead to innovation in the business sector. The aim of the book is to guide scholars and business consultants on IT and business frameworks that can help new and existing organizations navigate the challenges posed by disruptive technologies to create a competitive advantage. The reviews are contributed by experts in business and information technology.


The chapters cover diverse topics related to technological advancements and digital security measures. Chapter 1 offers insights into accessing and securing patient medical records through a blockchain-based framework, detailing research methodology, scalability, and standards. Chapter 2 discusses cyber threats in IoT-connected cars, addressing vulnerabilities, attack methods, and defense strategies. Chapter 3 focuses on malware analysis and detection using machine learning techniques. Chapter 4 emphasizes on securing IoT-based home automation. Chapter 5 presents an IoT policy and governance reference architecture to ensure integrity and security across devices. Chapter 6 explores organizational security improvements to prevent deepfake ransomware. Finally, Chapter 7 examines the use of machine learning in credit card fraud detection, discussing challenges and control layers.



Readership
Scholars, academics, business consultants, entrepreneurs.

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Veröffentlichungsjahr: 2024

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Table of Contents
BENTHAM SCIENCE PUBLISHERS LTD.
End User License Agreement (for non-institutional, personal use)
Usage Rules:
Disclaimer:
Limitation of Liability:
General:
FOREWORD
PREFACE
List of Contributors
Access and Secure Patient Medical Records using Blockchain Technology based Framework: A Review
Abstract
1. INTRODUCTION
2. RELATED WORK
3. RESEARCH METHODOLOGY
4. RESEARCH OBJECTIVE
5. RESEARCH QUESTION
6. CONDUCTING SEARCH
7. INCLUSION AND EXCLUSION CRITERIA
8. SEARCH AND RESULTS AND COLLECTION
9. KEYWORDING
10. QUALITY ASSESSMENT
11. Data Extraction and Classification
12. ASSESSMENTS OF RESEARCH QUESTIONS
13. SCALABILITY
14. STANDARDS
15. TRANSFORMATION
16. COMPLEXITY DISCUSSION
CONCLUSION
REFERENCES
Identifying Cyber Threats in IoT based Connected Cars for Enhanced Security
Abstract
1. INTRODUCTION
2. VULNERABILITIES
3. METHODS OF ATTACKS
3.1. Key Fob
3.2. Attack via Tesla App in Android Smartphone
3.3. Attack via Infotainment System
3.4. GPS Spoofing Attack
4. METHODS OF DEFENSE
4.1. Key Fob Hack
4.2. Tesla App
4.3. Infotainment System
4.4. GPS Spoof
5. CONCEPTUAL FRAMEWORK
CONCLUSION
REFERENCES
Malware Analysis and Malicious Activity Detection using Machine Learning
Abstract
1. INTRODUCTION
2. AIVA SYSTEM ARCHITECTURE
2.1. AIVA Core Components
2.1.1. Static Analysis
2.1.2. Supervised Machine Learning
2.1.3. VirusTotal Application Programming Interface (API)
3. RESULTS AND DISCUSSIONS
CONCLUSION
REFERENCES
Secure IoT based Home Automation by Identifying Vulnerabilities and Threats
Abstract
1. INTRODUCTION
2. SMART HOME IOT
2.1. Smart Homes Architecture
3. SECURITY VULNERABILITIES, THREATS AND RISKS
3.1. Vulnerabilities & Threats
3.2. Weak Credentials
3.3. Insecure Network Services/Hardware Exploitation
3.4. Internal Device Failures/Limitations
3.5. Insecure Ecosystem Interfaces
3.6. Inefficient Update Mechanisms and Insecure Components
3.7. Risks
4. BUSINESS CONTINUITY AND DISASTER RECOVERY
5. ORGANIZATIONAL SECURITY, AWARENESS AND INFORMATION SHARING
CONCLUSION
REFERENCES
IoT Policy and Governance Reference Architecture: Integrity and Security of Information Across IoT Devices
Abstract
1. INTRODUCTION
2. REFERENCE ARCHITECTURE OF IOT
3. IOT POLICY
4. IOT GOVERNANCE
5. FRAMEWORK (IDENTIFY, INSULATE, INSPECT AND IMPROVE FRAMEWORK)
CONCLUSION
REFERENCES
Organizational Security Improvement in Preventing Deepfake Ransomware
Abstract
1. INTRODUCTION
1.1. What is Deepfake?
1.2. How Deepfakes are Created?
1.3. Why Deepfakes were Created?
2. DEEPFAKE RANSOMWARE IMPACT AND POTENTIAL RISK TO THE ORGANIZATION
2.1. Customer’s Trust and Confidence
2.2. Social Engineering
2.3. C-Level Fraud
2.4. Extortion Against Influential Business Leaders
2.5. Tarnish Organisation's Reputation
2.6. Operational Impact
2.7. Market Stock Manipulation
2.8. The Financial Burden
2.9. Server Message Block (SMB)
3. RISK MANAGEMENT, BUSINESS CONTINUITY AND DISASTER RECOVERY TAKEN BY THE ORGANISATION TO HANDLE THE SITUATION
3.1. Risk Management
3.2. Business Continuity
3.2.1. Project Management (PM)
3.2.2. Risk Analysis and Review (RAR)
3.2.3. Business Impact Analysis (BIA)
3.2.4. Business Continuity Strategy (BCS)
3.2.5. Business Continuity Planning Process
3.2.6. Testing, Exercising, and Improving
3.2.7. Program Management
3.3. Disaster Recovery
3.3.1. Disaster Recovery Team
3.3.2. Review Emergency Kit
3.3.3. Review Contact List
3.3.4. Identifying Alternative Suppliers and Facilities
3.3.5. Includes Business Impact Analysis
3.3.6. Inventory Check List of Physical Assets
3.3.7. Inventory Check List of Logical Assets
3.3.8. Communication Plan
3.3.9. Data Backup Plans
3.3.10. Testing the Disaster Recovery Plan
3.3.11. AI in Disaster Recovery
4. DEFENCE TECHNIQUES
4.1. Comprehensive Data Backup and Recovery Plan
4.2. Inconsistencies
4.3. Limitation of Voice and Images
4.4. Multi-factor Authentication
4.5. Restriction of Deepfake Tools
4.6. Isolate Infected Devices
4.7. Intrusion Prevention Software
4.8. AI and Blockchain Detection Technology
4.9. Content Authenticity Initiative (CAI)
4.10. Systems and Software Updates
4.11. Enable Anti-Virus
4.12. Server Message Block (SMB)
5. AWARENESS OF THE DEEPFAKES RANSOMWARE
5.1. Email Scams
5.2. Malware
5.3. Password Security
5.4. Removable Media
5.5. Safe Internet Habits
5.6. Data Management and Privacy
5.7. Inconsistencies
5.8. Security Protocols Act
5.9. Considering the Source
CONCLUSION
REFERENCES
Use of Machine Learning in Credit Card Fraud Detection
Abstract
1. INTRODUCTION
2. CONTROL LAYERS IN CREDIT CARD FRAUD DETECTION SYSTEM
3. TYPES OF CREDIT CARD FRAUD DETECTION SYSTEM
3.1. Machine Learning Techniques
3.2. Selection of Suitable Techniques for Credit Card Fraud Detection
4. CREDIT CARD FRAUD DETECTION CHALLENGES
5. DISCUSSION
CONCLUSION
REFERENCES
Digital Innovation Adoption: Architectural Recommendations and Security SolutionsEdited ByMuhammad Ehsan RanaSchool of Computer Science Asia Pacific University of Technology & Innovation Kuala Lumpur Malaysia& Manoj JayabalanSchool of Computer Science & Mathematics

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FOREWORD

I am delighted to write this foreword because I believe deeply in the importance of the topics and of high quality of the contents. There is latest and so much useful information being delivered into its 15 chapters which should not be missed. Thus it gives me a great pleasure to contribute this foreword.

As I reviewed the manuscript prior to writing this foreword, I was impressed by many unique features that I would like to share with you. The book explores the important aspect of the architectural requirements including emerging technologies and security-based concerns for digital innovation adoption. This work would be an important resource of exposure towards the Internet-of-Thing (IoT) and Artificial Intelligence (AI) in various important application domains.

Smart Cities and 5G Networks highlighted the advantages and disadvantages of radio and device-to-device in the context of multiple IoT use cases. IoT in Waste Management introduced an intelligent smart bin system to automate waste handling and management to contribute to green technology. Stock Monitoring System Using IoT Based Automation provided a set of recommendations for a hypermarket stock monitoring system using IoT automation. Secure Healthcare Using Blockchain Technology reviewed blockchain architecture in a health domain in order to secure patients’ medical records. E-Voting System Using Blockchain Technology implemented blockchain for e-voting systems of medium and large-scale size.

Decentralised News Using Blockchain Technology explained the implementation of blockchain via a decentralised application to combat misinformation. Cyber Threats in IoT-based Connected Cars exposed vulnerabilities for IoT-based connected cars and their implications. The use of IoT in Contact Tracing: Vulnerabilities and Countermeasures reviewed contact tracing application with IoT. AI-based Intrusion Detection System for IoT Security proposed a solution for security treats for IoT network with Intrusion Detection System. Fake News Detection Using Data Mining Approaches introduced a data mining as a technique to predict fake news.

EEG Signal Classification Using AI Techniques analysed the classification methods for EEG signals. Malware Analysis and Malicious Activity Detection Using Machine Learning reviewed AI techniques to protect and prevent security threats in the IT infrastructure. Interestingly the authors have proposed a machine-learning based detection system to classify suspicious objects. Security Vulnerabilities and Threats for IoT-based Home revealed the security vulnerabilities for the smart home concept and its protection. IoT Policy and Governance Reference Architecture discussed IoT reference architecture, policy and governance for the integrity and security of the information being transmitted within the IoT ecosystem. Organizational Security Improvement in Preventing Deepfake Ransomware highlighted the impact of deep fake ransomware to the organisation and its protection.

The content provides a widely useful compilation of ideas, cases, innovative approaches, and practical strategies for enhancing digital innovation adoption mainly covering the architecture and security. This book should be read by anyone including researchers, educators, industry practitioners and technology specialists who intend to learn, practice, and adopt innovative technology in their respective areas of interest to bring digital transformation by indulging in the architectural requirements and security concerns.

Wan Nurhayati Wan Ab. Rahman, Ph.D Faculty of Computer Science and Information Technology Universiti Putra Malaysia Selangor Malaysia

PREFACE

Digital innovation assists organizations in innovating and driving services to bespoke clients that leverage high value. The integration of major disruptive technologies such as cloud, big data, IoT and blockchain has ignited the retransformation of the entire industrial arena. As a result of this convergence of technologies, organisations need to go through a mandatory process of change at a rapid pace. Every industry, from agriculture to manufacturing, transportation to education, pharmaceutical to health services, is forced to be revolutionised using innovative approaches. Organisation's products, services, and operations need to embrace a technological shift to differentiate themselves in the competitive arena and satisfy their customers' ever-increasing needs. Billions of digitally enabled devices will create the dawn of a whole new era by utilising their sensing, processing, and connectivity power through the use of the Internet of Things (IoT). Consumer-based companies rely heavily on mobile devices to deliver personal experiences. Cloud is redefining the way businesses were previously done. It is a paradigm shift from traditional IT to a more efficient, scalable, and secure infrastructure. Blockchain offers a decentralised structure that demonstrates transparency and trust and provides individual control of data. Organisations need to lay down the sophisticated architectural requirements of the proposed solutions to take advantage of the evolving digital technology. The extensive reliance on these technologies has also possessed some security challenges for providers and consumers. The ubiquitous data access via multiple end-user devices has paved the way for security and cyber threats. As information security is critical for contemporary businesses, organisations have an essential role in protecting the information to deal with highly augmented security and privacy threats. This book is intended to explore the architectural requirements of these digitally transformed systems by adopting emerging technologies and examining security-based concerns considering the vulnerabilities and countermeasures for these systems.

Muhammad Ehsan Rana School of Computer Science Asia Pacific University of Technology & Innovation Kuala Lumpur Malaysia &Manoj Jayabalan School of Computer Science & Mathematics Liverpool John Moores University Liverpool UK