Big Data Analytics and Computational Intelligence for Cybersecurity

Preface
Contents
About the Editors
Cybersecurity in Communication Networks: Challenges and Opportunities
New Advancements in Cybersecurity: A Comprehensive Survey
1 Introduction
2 Background Study
2.1 Prevention
2.2 Surveillance
2.3 Detection
2.4 Response
2.5 Deception
2.6 Computational Intelligence for Cyber Security
3 Conclusion
References
CPSs Communication Using 5G Network in the Light of Security
1 Introduction
2 Literature Review
3 Methodology
4 Results and Discussion
5 Conclusion
References
A Survey on Security Aspects in RPL Protocol Over IoT Networks
1 Introduction
2 RPL Overview
3 Related Work
4 Securing the Protocol
5 Conclusion
References
Analysis of Cybersecurity Risks and Their Mitigation for Work-From-Home Tools and Techniques
1 Introduction
2 Related Work
3 Zero Trust Model
3.1 Traditional Networks Shortcomings
3.2 Principle of Zero Trust
3.3 Logical Components of Zero Trust Architecture
4 Secure Access Service Edge “SASE”
5 Cybersecurity Framework for Work-From-Home
6 SASE and ZTN Combination
7 Trust Management and Challenges in ZTN
8 Challenges for SASE
9 Security Analysis of Tools and Techniques to Support IT Services
10 Conclusion
References
A Systemic Security and Privacy Review: Attacks and Prevention Mechanisms Over IoT Layers
1 Introduction
1.1 IoT Security Challenges
1.2 Key Role of Layers in IoT
1.3 Physical Layer/Perception Layer
1.4 Network Layer
1.5 Application Layer
2 Attacks and Their Countermeasures on Layer Architecture
2.1 Network Layer
2.2 Network Layer Attacks
2.3 Sinkhole Attack
2.4 Sniffing Attack
2.5 Man-in-Middle Attack
2.6 DOS Attack
2.7 Perception Layer
2.8 Application Layer
3 Open Issues
4 Conclusion
References
Software-Defined Networking Security: A Comprehensive Review
1 Introduction
2 Overview of SDN
2.1 Definition and Concept
2.2 SDN Architecture
2.3 Benefits of SDN
3 Towards a New Approach
3.1 State of Traditional Networks
3.2 Limits of the Current Architecture
3.3 New Needs and Challenges
4 Programmable Networks
4.1 OpenFlow Concept
4.2 Why OpenFlow?
4.3 OpenFlow Protocol
4.4 Component of an OpenFlow Network
4.5 SDN Controllers
5 SDN Security Based on IDS
5.1 Definition of IDS
5.2 Types of IDS
5.3 Methods of Detections of IDS
5.4 Examples of IDS
6 Literature Review
6.1 Mitigation Techniques Without the Use of IDS
6.2 Mitigation Techniques with the Use of IDS
6.3 Discussion
7 Conclusion
References
Detection of Security Attacks Using Intrusion Detection System for UAV Networks: A Survey
1 Introduction
2 Literature Survey
3 Architectural Design of UAV-Networks
4 Routing Protocols for FANETs
4.1 Proactive Protocols for UAV-Network
4.2 Reactive Protocols for UAV-Network
4.3 Hybrid Protocols for UAV-Network
5 Intrusion Detection System for UAV-Networks
5.1 Network-Intrusion-Detection-System
5.2 Host-Based-Intrusion-Detection-System
5.3 Signature-Based-Intrusion-Detection-System
5.4 Anomaly-Based-Intrusion-Detection-System
5.5 Hybrid-Intrusion-Detection-System
5.6 Protocol-Based-Intrusion-Detection-System
5.7 Application-Protocol-Based-Intrusion-Detection-System
6 Security Attacks on UAV-Networks
6.1 Denial of Service (Dos)
6.2 Distributed Deinal of Service (DDOS)
6.3 Sybil Attack
6.4 Domain Name System (DNS) Attack
7 Mobility Models for UAV-Networks
8 Future Directions
9 Conclusion
References
Computational Intelligence for Cybersecurity
Role of Computational Intelligence in Cybersecurity
1 Introduction
2 Motivation
3 Literature Review
4 Introduction to Cybersecurity
5 CIA Triad
5.1 Confidentiality
5.2 Integrity
5.3 Availability
6 Threats/Attacks in Cybersecurity
6.1 Spoofing
6.2 DOS
6.3 Ping of Death (POD)
7 Monitoring and Assessing Vulnerabilities
8 Intrusion Detection Systems
8.1 Signature-Based Detection
8.2 Anomaly-Based Detection
8.3 Hybrid Based Detection
9 Conclusion
References
Computational Intelligence Techniques for Cyberspace Intrusion Detection System
1 Overview
2 Introduction
3 Motivation
4 Literature Review
5 Different Algorithms for Computational Intelligence
5.1 Method Based on Anomaly
5.2 Method Based on Artificial Intelligence
5.3 Method Based on Machine Learning Methods
6 Conclusion
References
A Comparative Analysis of Intrusion Detection in IoT Network Using Machine Learning
1 Introduction
2 Related Work
3 Methodology
3.1 Machine-Learning Algorithms for Anomaly Detection
3.2 Preprocessing
3.3 Feature Selection
3.4 Classification
4 Experiments and Results
4.1 Dataset Description
4.2 Performance Metrics
4.3 Confusion Matrix
4.4 Performance of ML Technique
5 Conclusion
References
Blockchain Enabled Artificial Intelligence for Cybersecurity Systems
1 Introduction
1.1 Medium Storage Decentralization
1.2 Securing the IoT Devices
1.3 Keeping Secret Messages Safe
1.4 Cyber-Physical Architecture Evaluation
1.5 Reducing the Cyber-Attacks
1.6 Data Communication Security
1.7 Foundations of Software Applications
2 Introduction to Artificial Intelligence for Cybersecurity Systems
2.1 Supply-Chain Management
2.2 Healthcare and Life Sciences
2.3 Financial and Economic Services
2.4 Predictive Analytics for Cyber-Attacks
2.5 Chatbots Assistants
2.6 Preventing Data Manipulation
2.7 Data Security and Transparency
3 Open Challenges for Blockchain Enabled AI Solutions for Cybersecurity
3.1 Side Chains and Flexibility
3.2 Confidentiality
3.3 Security Flaws in Smart Contracts
3.4 Blockchain Security
3.5 Absence of Compliance, Standardization and Protocols
3.6 Governance
3.7 Quantum Computing
4 Conclusion
References
Approaches for Visualizing Cybersecurity Dataset Using Social Network Analysis
1 Introduction
1.1 Visualization
1.2 Visualization in Cybersecurity
1.3 Problem Statement
1.4 Scope
2 Social Network Analysis Approaches
2.1 Social Network Approaches and Datasets
2.2 Gephi
2.3 Pajek
2.4 Tulip
2.5 Cybersecurity Breaches Dataset
3 Methodology
3.1 Collection of Data
4 Visualization of Dataset
4.1 Gephi Visualization
4.2 Pajek Visualization
4.3 Tulip Visualization
5 Analysis
5.1 Gephi
5.2 Results
5.3 Analysis
5.4 Limitation
5.5 Pajek
5.6 Results
5.7 Analysis
5.8 Limitation
5.9 Tulip
5.10 Results
5.11 Analysis
5.12 Limitation
References
Big Data Analytics and Applications
Data Footprinting in Big Data
1 Introduction
2 Foot Printing
2.1 Company Web Page
2.2 Related Organization
2.3 Company Employee
2.4 Current Affairs
2.5 Archive Information
2.6 Search Engines
2.7 Google Hacking
2.8 Metadata Analyzer
2.9 Internet Facing Devices
3 Objectives of Footprinting
4 Footprinting Methodologies
5 Tools
6 Footprinting Threats
7 Conclusion
References
An Investigation of Unmanned Aerial Vehicle Surveillance Data Processing with Big Data Analytics
1 Introduction
1.1 Applications of UAV
1.2 Advantages of UAV
2 Application of Big Data
3 UAV Data Management
3.1 UAV Drone Data Processing
3.2 Process of UAV Data Collection and Analysis
3.3 Process Flow in UAV Data Processing
3.4 Dataflow in UAV Data Processing
3.5 Big Data Management Techniques in UAV Data Processing
4 Application of Big Data Management in UAV
5 Background Study
6 Research Challenges in UAV Data Processing
7 Conclusion
References
Big Data Mining Using K-Means and DBSCAN Clustering Techniques
1 Introduction
2 Resources and Tools
3 Big Data Analytics
4 Proposed Method
4.1 Web Server Log File
4.2 Data Preprocessing
4.3 Pattern Discovery
5 Results and Discussion
5.1 Data Pre-processing
5.2 Pattern Discovery
6 Conclusion
7 Recommendations
8 Dedication
References
IoT Security in Smart University Systems
1 Introduction
2 Smart Campus
2.1 Smart Universities
2.2 Smart Universities Technologies and Connectivity
2.3 Smart University Vulnerabilities
2.4 Smart University Susceptible Attacks
2.5 Development of IoT Security Mechanisms in Smart Universities Environments
3 Discussion
4 Conclusion
References
The Impact of Big Data and IoT for Computational Smarter Education System
1 Introduction
2 Architecture of Smart Learning Environment
2.1 3-Tier Architecture
3 Key Functions of Smart Computing 5 A’s
3.1 Action
3.2 Auditability
3.3 Alternativeness
3.4 Analysis
3.5 Awareness
4 Smart Environment
5 IOT Applications
5.1 Significance of IOT in Education
5.2 Smart Education
5.3 Challenges of Smarter Education
5.4 Effect of Smart Classroom on Student Achievement at Higher Education
5.5 Existing Applications of IOT in Education
5.6 General Challenges of IOT in Education
6 Conclusion
References
Transformation in Health-Care Services Using Internet of Things (IoT): Review
1 Introduction
2 Overview of IoT in Health-Care
3 Literature Review
4 Architecture of Health-Care IoT
4.1 Physical Layer
4.2 Network Layer
4.3 Application Layer
5 Technologies of IoT in Health-Care
5.1 Identification Technology
5.2 Communication Technology
5.3 Location Technology
6 Applications of IoT in Health-Care
6.1 Remote Monitoring
6.2 Depression and Mood Monitoring
6.3 Sleep Monitoring
6.4 Elderly Care
6.5 Digital Hospital
6.6 Wearable Devices
6.7 Drug Monitoring
6.8 Connected Inhalers
6.9 Ingestible Sensors
7 Challenges of IoT in Health-Care
7.1 Security
7.2 Acceptability and Adoption
7.3 Data Management
7.4 Data Overload
7.5 Integration
8 Conclusion
References
A Survey of Deep Learning Methods for Fruit and Vegetable Detection and Yield Estimation
1 Introduction
2 Background Study
2.1 Computer Vision and Agriculture
3 Literature Review of Surveys
3.1 Deep Learning Framework for the Detection of Fruit and Vegetable
4 Datasets
5 Performance Assessment Metrics
6 Conclusion
6.1 Key Challenges
6.2 Future Directions
References
Bird Calls Identification in Soundscape Recordings Using Deep Convolutional Neural Network
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset
3.2 Mel-Spectrograms
3.3 Proposed CNN Model
3.4 Model Training
4 Experiments and Results
5 Conclusion and Future Work
References