Cyber Security and Network Security

Description

CYBER SECURITY AND NETWORK SECURITY Written and edited by a team of experts in the field, this is the most comprehensive and up-to-date study of the practical applications of cyber security and network security for engineers, scientists, students, and other professionals. Digital assaults are quickly becoming one of the most predominant issues on the planet. As digital wrongdoing keeps on expanding, it is increasingly more important to investigate new methodologies and advances that help guarantee the security of online networks. Ongoing advances and innovations have made great advances for taking care of security issues in a methodical manner. In light of this, organized security innovations have been delivered so as to guarantee the security of programming and correspondence functionalities at fundamental, improved, and engineering levels. This outstanding new volume covers all of the latest advances, innovations, and developments in practical applications for cybersecurity and network security. This team of editors represents some of the most well-known and respected experts in the area, creating this comprehensive, up-to-date coverage of the issues of the day and state of the art. Whether for the veteran engineer or scientist or a student, this volume is a must-have for any library. Cover Half-Title Page Series Page Title Page Copyright Page Dedication Contents Preface Acknowledgments 1. Securing Cloud-Based Enterprise Applications and Its Data 1.1 Introduction 1.2 Background and Related Works 1.3 System Design and Architecture 1.3.1 Proposed System Design and Architecture 1.3.2 Modules 1.3.2.1 Compute Instances 1.3.2.2 API Gateway 1.3.2.3 Storage Bucket (Amazon S3) 1.3.2.4 Lambda 1.3.2.5 Load Balancer 1.3.2.6 Internet Gateway 1.3.2.7 Security Groups 1.3.2.8 Autoscaling 1.3.2.9 QLDB 1.3.2.10 NoSQL Database 1.3.2.11 Linux Instance and Networking 1.3.2.12 Virtual Network and Subnet Configuration 1.4 Methodology 1.4.1 Firewall 1.4.2 Malware Injection Prevention 1.4.3 Man-in-the-Middle Prevention 1.4.4 Data at Transit and SSL 1.4.5 Data Encryption at Rest 1.4.6 Centralized Ledger Database 1.4.7 NoSQL Database 1.4.8 Linux Instance and Server Side Installations 1.5 Performance Analysis 1.5.1 Load Balancer 1.5.2 Lambda (For Compression of Data) 1.5.3 Availability Zone 1.5.4 Data in Transit (Encryption) 1.5.5 Data in Rest (Encryption) 1.6 Future Research Direction 1.7 Conclusion References 2. High-Performance Computing-Based Scalable “Cloud Forensics-as-a-Service” Readiness Framework Factors—A Review 2.1 Introduction 2.2 Aim of the Study 2.3 Motivation for the Study 2.4 Literature Review 2.5 Research Methodology 2.6 Testing Environment Plan 2.7 Testing 2.7.1 Scenario 1: Simultaneous Imaging and Upload and Encryption 2.7.2 Scenario 2: Real-Time Stream Processing 2.7.3 Scenario 3: Remote Desktop Connection, Performance Test 2.8 Recommendations 2.9 Limitations of Present Study 2.10 Conclusions 2.11 Scope for the Future Work Acknowledgements References 3 Malware Identification, Analysis and Similarity 3.1 Introduction 3.1.1 Goals of Malware Analysis and Malware Identification 3.1.2 Common Malware Analysis Techniques 3.2 Background and Related Works 3.3 Proposed System Design Architecture 3.3.1 Tool Requirement, System Design, and Architecture 3.3.1.1 For Static Malware Analysis 3.3.1.2 For Dynamic Malware Analysis 3.4 Methodology 3.5 Performance Analysis 3.6 Future Research Direction 3.7 Conclusion References 4. Robust Fraud Detection Mechanism 4.1 Introduction 4.2 Related Work 4.2.1 Blockchain Technology for Online Business 4.2.2 Validation and Authentication 4.2.3 Types of Online Shopping Fraud 4.2.3.1 Software Fraudulent of Online Shopping 4.2.4 Segmentation/Authentication 4.2.4.1 Secure Transaction Though Segmentation Algorithm 4.2.4.2 Critical Path Segmentation Optimization 4.2.5 Role of Blockchain Technology for Supply Chain and Logistics 4.3 Conclusion References 5. Blockchain-Based Identity Management Systems 5.1 Introduction 5.2 Preliminaries 5.2.1 Identity Management Systems 5.2.1.1 Identity Factors 5.2.1.2 Architecture of Identity Management Systems 5.2.1.3 Types of Identity Management Systems 5.2.1.4 Importance of Identity Management Systems 5.2.2 Blockchain 5.2.2.1 Blockchain Architecture 5.2.2.2 Components of Blockchain Architecture 5.2.2.3 Merkle Tree 5.2.2.4 Consensus Algorithm 5.2.2.5 Types of Blockchain Architecture 5.2.3 Challenges 5.3 Blockchain-Based Identity Management System 5.3.1 Need for Blockchain-Based Identity Management Systems 5.3.2 Approaches for Blockchain-Based Identity Management Systems 5.3.3 Blockchain-Based Identity Management System Implementations 5.3.4 Impact of Using Blockchain-Based Identity Management on Business and Users 5.3.5 Various Use Cases of Blockchain Identity Management 5.4 Discussion 5.4.1 Challenges Related to Identity 5.4.2 Cost Implications 5.5 Conclusion 5.6 Future Scope References 6. Insights Into Deep Steganography: A Study of Steganography Automation and Trends 6.1 Introduction 6.2 Convolution Network Learning 6.2.1 CNN Issues 6.3 Recurrent Neural Networks 6.3.1 RNN Forward Propagation 6.4 Long Short-Term Memory Networks 6.4.1 LSTM Issues 6.5 Back Propagation in Neural Networks 6.6 Literature Survey on Neural Networks in Steganography 6.6.1 TS-RNN: Text Steganalysis Based on Recurrent Neural Networks 6.6.2 Generative Text Steganography Based on LSTM Network and Attention Mechanism with Keywords 6.6.3 Graph-Stega: Semantic Controllable Steganographic Text Generation Guided by Knowledge Graph 6.6.4 RITS: Real-Time Interactive Text Steganography Based on Automatic Dialogue Model 6.6.5 Steganalysis and Payload Estimation of Embedding in Pixel Differences Using Neural Networks 6.6.6 Reversible Data Hiding Using Multilayer Perceptron–Based Pixel Prediction 6.6.7 Neural Network–Based Steganography Algorithm for Still Images 6.7 Optimization Algorithms in Neural Networks 6.7.1 Gradient Descent 6.7.1.1 GD Issues 6.7.2 Stochastic Gradient Descent 6.7.2.1 SGD Issues 6.7.3 SGD with Momentum 6.7.4 Mini Batch SGD 6.7.4.1 Mini Batch SGD Issues 6.7.5 Adaptive Gradient Algorithm 6.8 Conclusion References 7. Privacy Preserving Mechanism by Application of Constrained Nonlinear Optimization Methods in Cyber-Physical System 7.1 Introduction 7.2 Problem Formulation 7.3 Proposed Mechanism 7.4 Experimental Results 7.5 Future Scope 7.6 Conclusion References 8. Application of Integrated Steganography and Image Compressing Techniques for Confidential Information Transmission 8.1 Introduction 8.2 Review of Literature 8.3 Methodology Used 8.4 Results and Discussion 8.5 Conclusions References 9. Security, Privacy, Risk, and Safety Toward 5G Green Network (5G-GN) 9.1 Introduction 9.2 Overview of 5G 9.3 Key Enabling Techniques for 5G 9.4 5G Green Network 9.5 5G Technologies: Security and Privacy Issues 9.5.1 5G Security Architecture 9.5.2 Deployment Security in 5G Green Network 9.5.3 Protection of Data Integrity 9.5.4 Artificial Intelligence 9.6 5G-GN Assets and Threats 9.7 5G-GN Security Strategies and Deployments 9.8 Risk Analysis of 5G Applications 9.9 Countermeasures Against Security and Privacy Risks 9.9.1 Enhanced Mobile Broadband 9.9.2 Ultra-Reliable Low Latency Communications 9.10 Protecting 5G Green Networks Against Attacks 9.11 Future Challenges 9.12 Conclusion References 10. A Novel Cost-Effective Secure Green Data Center Solutions Using Virtualization Technology 10.1 Introduction 10.2 Literature Survey 10.2.1 Virtualization 10.3 Problem Statement 10.3.1 VMware Workstation 10.4 Green it Using Virtualization 10.5 Proposed Work 10.5.1 Proposed Secure Virtual Framework 10.6 Conclusion Acknowledgments References 11. Big Data Architecture for Network Security 11.1 Introduction to Big Data 11.1.1 10 V’s of Big-Data 11.1.2 Architecture of Big Data 11.1.3 Big Data Access Control 11.1.4 Classification of Big Data 11.1.4.1 Structured Data 11.1.4.2 Unstructured Data 11.1.4.3 Semi-Structured Data 11.1.5 Need of Big Data 11.1.6 Challenges to Big Data Management 11.1.7 Big Data Hadoop 11.1.8 Big Data Hadoop Architecture 11.1.9 Security Factors 11.1.10 Performance Factors 11.1.11 Security Threats 11.1.12 Big Data Security Threats 11.1.13 Distributed Data 11.1.14 Non-Relational Databases 11.1.15 Endpoint Vulnerabilities 11.1.16 Data Mining Solutions 11.1.17 Access Controls 11.1.18 Motivation 11.1.19 Importance and Relevance of the Study 11.1.20 Background History 11.1.21 Research Gaps 11.2 Technology Used to Big Data 11.2.1 MATLAB 11.2.2 Characteristics of MATLAB 11.2.3 Research Objectives 11.2.4 Methodology 11.3 Working Process of Techniques 11.3.1 File Splitter 11.3.2 GUI Interface for Client 11.3.3 GUI Interface for Server 11.3.4 Encrypted File 11.4 Proposed Work 11.4.1 Working 11.4.2 Process Flow of Proposed Work 11.4.3 Proposed Model 11.5 Comparative Analysis 11.5.1 Time Comparison 11.5.2 Error Rate Comparison 11.5.3 Packet Size Comparison 11.5.4 Packet Affected Due to Attack 11.6 Conclusion and Future Scope 11.6.1 Conclusion 11.6.2 Future Scope References About the Editors Index Also of Interest