Security and Organization within IoT and Smart Cities

Cover
Half Title
Title Page
Copyright Page
Dedication
Table of Contents
Preface
Acknowledgement
About the Editors
Contributors
Chapter 1 An Overview of the Artificial Intelligence Evolution and Its Fundamental Concepts, and Their Relationship with IoT Security
1.1 Introduction
1.2 Artificial Intelligence Fundamental Concepts
1.3 AI Technologies and Evolution
1.4 AI Technologies and IoT
1.5 Discussion
1.6 Future Trends
1.7 Conclusions
References
Chapter 2 Smart City: Evolution and Fundamental Concepts
2.1 Smart City
2.2 Characteristics of a Smart City
2.2.1 Smart Energy
2.2.2 Smart Data
2.2.3 Smart Transport
2.2.4 Smart Infrastructure
2.2.5 Connected Devices
2.2.6 Connected Mobility
2.3 Components of Smart City
2.3.1 Economy
2.3.2 Governance
2.3.3 Environment
2.3.4 Living
2.3.5 People
2.3.6 Mobility
2.4 Roadmap
2.5 Application of Smart Cities
2.5.1 Health Management
2.5.2 Smart Transportation
2.5.3 Waste Management
2.5.4 Surveillance
2.5.5 Water Management
2.5.6 Smart Parking
2.5.7 Data Monitoring
2.5.7.1 Three Layers of Data
2.5.7.2 Issues for the City Management
2.5.7.3 Data Challenges
2.5.8 Self-Driving Cars
2.5.9 Smart Street Lightning
2.5.9.1 Key Takeaways for Considering Smart Lighting
2.5.10 Emergency Services
2.5.11 Smart Energy Management
2.5.12 Smart Agriculture
2.5.12.1 IoT Applications for Smart Farming
2.5.13 Wearable Devices
2.5.14 Smart Education
2.5.15 Underground Tunnelling
2.5.15.1 Tunnelling Renaissance
2.6 Future of Smart Cities
2.6.1 Innovative Technologies for Smart City
2.6.2 Better Quality of Life
2.7 Technologies Evolving Smart Cities
2.7.1 Smart Cities 1.0: Surveillance, Digital and Eco-Friendly Cities
2.7.2 Smart Cities 2.0: Sustainable, and Resilient Cities
2.7.3 Smart Cities 3.0: Green, Rightful Cities
References
Chapter 3 Advances in AI-Based Security for Internet of Things in Wireless Virtualization Environment
3.1 Introduction
3.2 IoT Data Characteristics
3.3 Different types of security attacks in the IoT network
3.4 Smart Home Security Threats
3.5 Different AI/ML models to Combat IoT security attacks
3.5.1 classification
3.5.1.1 KNN (K-nearestneighbors)
3.5.1.2 Classification based on naïve Bayes
3.5.1.3 Support Vector Machine (SVM)
3.6 Summary
References
Chapter 4 A Conceptual Model for Optimal Resource Sharing of Networked Microgrids Focusing Uncertainty: Paving the Path to Eco-Friendly Smart Cities
4.1 Introduction
4.2 Related Work
4.3 Conceptual System Model
Algorithm 1-1:
4.4 Conclusion
References
Chapter 5 A Novel Framework for a Cyber Secure Smart City
5.1 Introduction
5.2 Cybersecurity in Smart City
5.3 Security in Governance, Social and Economic Perspective
5.3.1 Administration Factors
5.3.2 Need for Security Testing
5.3.3 Dangers to Basic Foundations
5.3.4 Smart Mobility Security and Protection Necessities
5.3.5 Vitality and Utility Improvement
5.3.6 Social and Monetary Components
5.3.7 Challenges in Smart City Communication
5.3.8 Singular Privacy
5.4 Privacy Protection in Smart Cities
5.4.1 Privacy Models
5.5 Cyber Threats and Countermeasures in Smart Cities
5.6 A Novel Framework for Cyber Secure Smart City
5.7 Conclusion
References
Chapter 6 Contemplating Security Challenges and Threats for Smart Cities
6.1 Introduction
6.2 Privacy AND Security Concerns In Smart City
6.2.1 Why Is Privacy a Concern in Smart City?
6.2.2 Consequences of Privacy Concerns
6.2.2.1 Bluetooth Technology
6.2.2.2 Health Sector
6.2.2.3 Big Data Analytics
6.2.2.4 Cloud System
6.2.2.5 Internet of Things
6.2.2.6 Smart Card
6.2.2.7 Smart Tourism
6.2.2.8 Drones
6.2.2.9 Mobile Applications
6.2.2.10 E-Govennance
6.2.2.11 Online Social Networks
6.2.2.12 Biometrics
6.2.3 Concept and Cardinals of Smart City in the World
6.2.4 Why Is Security a Concern in Smart City?
6.2.5 Security Threats and Challenges [55]
6.2.6 Cybersecurity Challenges in Smart Cities [54]
6.2.7 Countermeasures and Probable Strategy for Security Concerns [57]
6.2.8 Countermeasures for Privacy Concerns
6.2.8.1 Sensing as a Service Model
6.2.8.2 5D Model for Privacy
6.2.8.3 User Awareness
6.2.8.4 Privacy Protection in RFID
6.2.8.5 Data Aggregation
6.2.8.6 Stakeholder Model
6.2.8.7 2 × 2 Framework
6.2.8.8 Mobile Cloud Framework
6.2.8.9 Changing Pseudonyms in Intelligent Transport System
6.2.8.10 Homomorphic Encryption
6.2.8.11 Three-Layer Model
6.2.8.12 Linear Algebra
6.2.8.13 Continuous Streaming Data
6.2.8.14 Protection of DBMS from Insider Attacks
6.2.8.15 Anonymization of Transaction Data
6.2.8.16 D-Mash Model
6.2.8.17 Lattice Based Secure Cryptosystem
6.2.8.18 Taxonomy Diagram
6.3 Tabular representations
6.4 Open Issues
6.5 Conclusions and Recommendations
References
Chapter 7 Self-Monitoring Obfuscated IoT Network
7.1 Introduction
7.2 Related Works
7.3 Proposed Method
7.3.1 The Inter-Module Steganography Protocol
7.3.1.1 Control Signals Embedding Technique
7.3.2 Behaviour Learning
7.4 Results and Analysis
7.5 Conclusion
References
Chapter 8 Introduction to Side Channel Attacks and Investigation of Power Analysis and Fault Injection Attack Techniques
8.1 Introduction
8.1.1 Brief History of Side ChannelAttacks
8.2 State of the Art in Hardware Security
8.2.1 Meltdown Attack
8.2.2 Spectre Attack
8.2.3 Acoustic Cryptanalysis
8.2.4 Page Cache Attack
8.3 Side Channel Attack Model
8.3.1 Classification of side channel attacks
8.3.1.2 Invasive vs Non-invasive:
8.4 Power Analysis Techniques
8.4.1 Simple Power Analysis and Differential Power Analysis
8.4.2 Differential Power Analysis
8.4.3 Correlation Power Analysis
8.4.3.1 Steps to Perform CPA Attack
8.4.4 Mutual Information Analysis
8.4.5 Horizontal and Vertical Power Attack
8.4.6 Combined Implementation Attack
8.4.6.1 Basic Principle of Combining Active and Passive Attacks
8.5 Non-Invasive Active Attacks
8.5.1 Fault Injection Attacks
8.5.2 Effects of Fault Injection Attacks
8.5.3 Effect of Fault Injection Propagation
8.6 Fault Injection Attacks
8.6.1 Power Tampering/Voltage Glitching
8.7 Hands-On-Experiments: Fault Injection Attacks
8.7.1 Objectives
8.7.2 Method
8.7.3 Leaning Outcome
8.8 Exercises
8.8.1 Short Answers Type Questions
References
Chapter 9 Collaborative Digital Forensic Investigations Model for Law Enforcement
9.1 Introduction
9.2 Literature Review
9.2.1 Definitions of Digital Forensics
9.2.2 Digital Forensics for Law Enforcement
9.2.3 The Evolution of Existing Digital Forensic Investigation (DFI) Models
9.2.4 ISO Standards
9.3 Towards a new Collaborative DFI Model
9.3.1 Why ROP Needs a New Model
9.3.2 Phases within the CDFIR Model
9.3.3 Readiness
9.3.4 Initialization
9.3.5 Acquisition
9.3.6 Investigation
9.3.7 Rules and Responsibilities RACI Matrix
9.3.8 Facilitating Collaboration
9.4 Conclusion and Recommendations
Acknowledgements
References
Chapter 10 Understanding Security Requirements and Challenges in the Industrial Internet of Things: A Review
10.1 Introduction
10.2 Privacy in IoT
10.2.1 Existing Solution and Discussion
10.3 Lightweight Cryptographic Framework for IoT
10.3.1 Existing Solution and Discussion
10.4 Conclusion
References
Chapter 11 5G Security and the Internet of Things
11.1 Introduction
11.2 Security Risks
11.3 Securing 5G
11.4 Future of 5G
11.5 Conclusion
References
Chapter 12 The Problem of Deepfake Videos and How to Counteract Them in Smart Cities
12.1 Introduction
12.2 How Deepfakes are Made
12.3 The motivation to create Deepfakes
12.4 The security concerns around Deepfakes
12.5 How Organisations are Counteracting the Use of Deep Fake Technology
12.6 Deepfakes and the Law
12.7 The Future of Deepfakes
12.8 Conclusion
References
Bibliography
Chapter 13 The Rise of Ransomware Aided by Vulnerable IoT Devices
13.1 Introduction
13.2 Attack Vectors
13.2.1 Email attachments and links
13.2.2 Online advertisements
13.2.3 Downloads
13.2.4 Water Hole Attacks
13.2.5 Exploit Kits
13.2.6 Botnets
13.3 Evolution of Ransomware
13.3.1 1989
13.3.2 2005
13.3.3 2006
13.3.4 2007
13.3.5 2012
13.3.6 2013
13.3.7 2014
13.3.8 2015
13.3.9 2016
13.3.10 2017
13.3.11 2018
13.4 How to secure against Ransomware
13.5 Future of Ransomware
13.6 Conclusion
References
Chapter 14 Security Issues in Self-Driving Cars within Smart Cities
14.1 Introduction
14.2 Risks Associated with Connected and Autonomous Vehicles
14.3 Future Developments
14.4 Conclusion
References
Chapter 15 Trust-Aware Crowd Associated Network-Based Approach for Optimal Waste Management in Smart Cities
15.1 Introduction
15.2 Related Work and Problem Definitions
15.2.1 Crowd Associated Network
15.3 Proposed Method
15.3.1 Overview
15.3.2 Network Architecture
15.3.3 Data Transmission
15.3.4 Waste Collection Route Optimization
15.3.4.1 Algorithm Flowchart (Figure 15.4)
15.3.5 Simulation Setup
15.3.5.1 Garbage Bin
15.3.5.2 Garbage Truck
15.3.5.3 Volunteer Agent
15.3.6 Evaluation
15.4 Results and Discussion
15.5 Conclusion and Future Work
Appendices
A1: Internal Design Detail
Test Report
References
Index