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Cyber Security and Digital Forensics
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Cyber Security and Digital Forensics
by Mangesh M. Ghonge, Sabyasachi Pramanik, Ramchandra Mangrulkar, Dac-Nhuong Le
Cyber Security and Digital Forensics
Cover
Title Page
Copyright
Preface
Acknowledgment
1 A Comprehensive Study of Security Issues and Research Challenges in Different Layers of Service-Oriented IoT Architecture
2 Quantum and Post-Quantum Cryptography
3 Artificial Neural Network Applications in Analysis of Forensic Science
4 A Comprehensive Survey of Fully Homomorphic Encryption from Its Theory to Applications
5 Understanding Robotics through Synthetic Psychology
6 An Insight into Digital Forensics: History, Frameworks, Types and Tools
7 Digital Forensics as a Service: Analysis for Forensic Knowledge
8 4S Framework: A Practical CPS Design Security Assessment & Benchmarking Framework
9 Ensuring Secure Data Sharing in IoT Domains Using Blockchain
10 A Review of Face Analysis Techniques for Conventional and Forensic Applications
11 Roadmap of Digital Forensics Investigation Process with Discovery of Tools
12 Utilizing Machine Learning and Deep Learning in Cybesecurity: An Innovative Approach
13 Applications of Machine Learning Techniques in the Realm of Cybersecurity
14 Security Improvement Technique for Distributed Control System (DCS) and Supervisory Control-Data Acquisition (SCADA) Using Blockchain at Dark Web Platform
15 Recent Techniques for Exploitation and Protection of Common Malicious Inputs to Online Applications
16 Ransomware: Threats, Identification and Prevention
Index
End User License Agreement
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Cyber Security and Digital Forensics
Table of Contents
Cover
Title Page
Copyright
Preface
Acknowledgment
1 A Comprehensive Study of Security Issues and Research Challenges in Different Layers of Service-Oriented IoT Architecture
1.1 Introduction and Related Work
1.2 IoT: Evolution, Applications and Security Requirements
1.3 Service-Oriented IoT Architecture and IoT Protocol Stack
1.4 Anatomy of Attacks on Service-Oriented IoT Architecture
1.5 Major Security Issues in Service-Oriented IoT Architecture
1.6 Conclusion
References
2 Quantum and Post-Quantum Cryptography
2.1 Introduction
2.2 Security of Modern Cryptographic Systems
2.3 Quantum Key Distribution
2.4 Post-Quantum Digital Signature
2.5 Conclusion and Future Directions
References
3 Artificial Neural Network Applications in Analysis of Forensic Science
3.1 Introduction
3.2 Digital Forensic Analysis Knowledge
3.3 Answer Set Programming in Digital Investigations
3.4 Data Science Processing with Artificial Intelligence Models
3.5 Pattern Recognition Techniques
3.6 ANN Applications
3.7 Knowledge on Stages of Digital Forensic Analysis
3.8 Deep Learning and Modelling
3.9 Conclusion
References
4 A Comprehensive Survey of Fully Homomorphic Encryption from Its Theory to Applications
4.1 Introduction
4.2 Homomorphic Encryption Techniques
4.3 Homomorphic Encryption Libraries
4.4 Computations on Encrypted Data
4.5 Applications of Homomorphic Encryption
4.6 Conclusion
References
5 Understanding Robotics through Synthetic Psychology
5.1 Introduction
5.2 Physical Capabilities of Robots
5.3 Traditional Psychology, Neuroscience and Future Robotics
5.4 Synthetic Psychology and Robotics: A Vision of the Future
5.5 Synthetic Psychology: The Foresight
5.6 Synthetic Psychology and Mathematical Optimization
5.7 Synthetic Psychology and Medical Diagnosis
5.8 Conclusion
References
6 An Insight into Digital Forensics: History, Frameworks, Types and Tools
6.1 Overview
6.2 Digital Forensics
6.3 Digital Forensics History
6.4 Evolutionary Cycle of Digital Forensics
6.5 Stages of Digital Forensics Process
6.6 Types of Digital Forensics
6.7 Evidence Collection and Analysis
6.8 Digital Forensics Tools
6.9 Summary
References
7 Digital Forensics as a Service: Analysis for Forensic Knowledge
7.1 Introduction
7.2 Objective
7.3 Types of Digital Forensics
7.4 Conclusion
References
8 4S Framework: A Practical CPS Design Security Assessment & Benchmarking Framework
8.1 Introduction
8.2 Literature Review
8.3 Medical Cyber Physical System (MCPS)
8.4 CPSSEC vs. Cyber Security
8.5 Proposed Framework
8.6 Assessment of Hypothetical MCPS Using 4S Framework
8.7 Conclusion
8.8 Future Scope
References
9 Ensuring Secure Data Sharing in IoT Domains Using Blockchain
9.1 IoT and Blockchain
9.2 IoT Application Domains and Challenges in Data Sharing
9.3 Why Blockchain?
9.4 IoT Data Sharing Security Mechanism On Blockchain
9.5 Conclusion
References
10 A Review of Face Analysis Techniques for Conventional and Forensic Applications
10.1 Introduction
10.2 Face Recognition
10.3 Forensic Face Recognition
10.4 Conclusion
References
11 Roadmap of Digital Forensics Investigation Process with Discovery of Tools
11.1 Introduction
11.2 Phases of Digital Forensics Process
11.3 Analysis of Challenges and Need of Digital Forensics
11.4 Appropriateness of Forensics Tool
11.5 Phase-Wise Digital Forensics Techniques
11.6 Pros and Cons of Digital Forensics Investigation Process
11.7 Conclusion
References
12 Utilizing Machine Learning and Deep Learning in Cybesecurity: An Innovative Approach
12.1 Introduction
12.2 Proposed Method
12.3 Experimental Studies and Outcomes Analysis
12.4 Conclusions and Future Scope
References
13 Applications of Machine Learning Techniques in the Realm of Cybersecurity
13.1 Introduction
13.2 A Brief Literature Review
13.3 Machine Learning and Cybersecurity: Various Issues
13.4 ML Datasets and Algorithms Used in Cybersecurity
13.5 Applications of Machine Learning in the Realm of Cybersecurity
13.6 Conclusions
References
14 Security Improvement Technique for Distributed Control System (DCS) and Supervisory Control-Data Acquisition (SCADA) Using Blockchain at Dark Web Platform
14.1 Introduction
14.2 Significance of Security Improvement in DCS and SCADA
14.3 Related Work
14.4 Proposed Methodology
14.5 Result Analysis
14.6 Conclusion
References
15 Recent Techniques for Exploitation and Protection of Common Malicious Inputs to Online Applications
15.1 Introduction
15.2 SQL Injection
15.3 Cross Site Scripting
15.4 Cross Site Request Forgery
15.5 Command Injection
15.6 File Inclusion
15.7 Conclusion
References
16 Ransomware: Threats, Identification and Prevention
16.1 Introduction
16.2 Types of Ransomwares
16.3 Ransomware Life Cycle
16.4 Detection Strategies
16.5 Analysis of Ransomware
16.6 Prevention Strategies
16.7 Ransomware Traits Analysis
16.8 Research Directions
16.9 Conclusion
References
Index
End User License Agreement
List of Illustrations
Chapter 1
Figure 1.1 IoT devices and platforms.
Figure 1.2 Security requirements and attacks in IoT.
Figure 1.3 General service-oriented architecture.
Figure 1.4 Service-oriented IoT architecture [49].
Figure 1.5 IoT protocol stack [52].
Figure 1.6 Attacks on software services.
Figure 1.7 Attacks on application layer and transport layer protocols.
Figure 1.8 Attacks on network layer protocols.
Figure 1.9 Attacks on link and physical layer protocols.
Chapter 2
Figure 2.1 BB84 key exchange protocol.
Figure 2.2 E91 key exchange protocol.
Chapter 3
Figure 3.1 Artificial neural network works as patterns in predicting information...
Figure 3.2 Deep learning enabled cyber forensic investigation analysis.
Figure 3.3 Hidato puzzle (Hidoku) matrix list (Kjellerstrand, 2015).
Figure 3.4 Role of artificial intelligence in data science.
Figure 3.5 Model for pattern recognition in forensic analysis.
Figure 3.6 Phases of digital investigation provides knowledge in forensic scienc...
Figure 3.7 Pattern recognition in deep learning algorithm.
Chapter 4
Figure 4.1 Working of homomorphic encryption.
Figure 4.2 Timeline of homomorphic encryption schemes from PHE to FHE.
Chapter 6
Figure 6.1 Flow process of digital forensics.
Figure 6.2 Cloud forensics flow process.
Figure 6.3 Flow process of mobile forensics.
Figure 6.4 Process of network forensics.
Figure 6.5 Evidence collection of storage devices.
Chapter 7
Figure 7.1 Digital forensics steps.
Figure 7.2 Branches of digital forensics.
Figure 7.3 Security threats of database system.
Figure 7.4 Forensic process of database systems.
Figure 7.5 Mobile device evidence proof extraction process.
Figure 7.6 Workflow of cloud forensic process.
Chapter 8
Figure 8.1 Flowchart with main sections and blocks inside each section.
Figure 8.2 Flowchart of MVM/quick assessment.
Figure 8.3 Flowchart of DCPS assessment.
Figure 8.4 Flowchart of HMSB assessment.
Figure 8.5 Flowchart of score calculation.
Figure 8.6 Flowchart of self benchmarking.
Figure 8.7 Hypothetical CPS’s block diagram.
Figure 8.8 Use case diagram of CIPMA system.
Chapter 9
Figure 9.1 Architecture of IoT.
Figure 9.2 Blockchain architecture.
Figure 9.3 IoT application domains.
Figure 9.4 Data shared IoT domains.
Chapter 10
Figure 10.1 Possible outcomes in the verification task [2].
Figure 10.2 Possible outcomes in the identification task [2].
Figure 10.3 Illumination variations [14].
Figure 10.4 Pose variations [14].
Figure 10.5 Facial expressions [14].
Figure 10.6 Architecture of forensic face recognition for manual and automated a...
Figure 10.7 Facial aging [26].
Figure 10.8 Facial marks [26].
Figure 10.9 Forensic sketch recognition [26].
Figure 10.10 Face recognition in video [26].
Figure 10.11 Partial occlusion features [26].
Figure 10.12 Glimpse of images captured from different datasets [27, 28].
Figure 10.13 Facial components [13].
Chapter 11
Figure 11.1 Entities affected by criminal activity.
Figure 11.2 Domain-wise hierarchy of digital forensics.
Figure 11.3 Phases of digital forensics process.
Figure 11.4 Elaboration of digital forensics phases.
Figure 11.5 Cyber-attack incidents with more than $1 million losses [13].
Figure 11.6 Growth of malware and phishing websites which are used to commit cri...
Figure 11.7 Evidence bag and faraday bags [15].
Figure 11.8 Procedure of data acquisition.
Figure 11.9 Disk partitioning for recovery of tampered and deleted file/document...
Figure 11.10 Sample of recovery of deleted data from USB using autopsy tool.
Figure 11.11 Collection of memory dump using Dumpit software.
Figure 11.12 Collection of information about the USB devices connected to a syst...
Figure 11.13 Recovery of JPEG image file with detailed information about startin...
Figure 11.14 Recovery of JPEG image file with detailed information about startin...
Figure 11.15 Analyzing the memory dump collected Dumpit in WinHex tool.
Figure 11.16 Image duplication of a USB using FTK toolkit.
Chapter 12
Figure 12.1 Set of experiments amidst many organizations.
Chapter 13
Figure 13.1 Modules of Microsoft’s security solutions.
Chapter 14
Figure 14.1 Industrial IoT: threats and countermeasures.
Figure 14.2 Hierarchal structure of IoT functionality layers.
Figure 14.3 An event-based approach for the protection of IoT networks.
Figure 14.4 Percentage of users targeted in different sectors.
Figure 14.5 Individual distribution of different types of crime rates.
Figure 14.6 Comparison of online transactions for last 10 years.
Chapter 16
Figure 16.1 Working of ransomware.
Figure 16.2 Types of ransomwares.
Figure 16.3 Ransomware life cycle.
Figure 16.4 Ransomware analysis.
List of Tables
Chapter 1
Table 1.1 Summary of application layer protocols.
Table 1.2 Summary of transport layer protocols and features.
Table 1.3 Summary of link layer and physical layer protocols (short range).
Table 1.4 Summary link layer and physical layer protocols (long range).
Table 1.5 Security issues in each layer of service oriented IoT architecture.
Table 1.6 Major threats in application - interface layer.
Table 1.7 Major threats in network layer.
Table 1.8 Major threats in sensing layer.
Chapter 2
Table 2.1 Security level of cryptographic systems.
Table 2.2 Round two candidates.
Table 2.3 Round three candidates.
Chapter 3
Table 3.1 Application of artificial neural networking in predicting diseases.
Chapter 4
Table 4.1 Libraries for various FHE implementation.
Table 4.2 Comparison of HE libraries based on various features.
Chapter 6
Table 6.1 Various forensics tools.
Chapter 8
Table 8.1 Points division for main sections.
Table 8.2 Points division for DCPS sections.
Table 8.3 Levels of system’s preparedness for handling attacks for cyber attacks...
Table 8.4 Cyber attacks & threats corpus of assessments.
Table 8.5 Levels of system’s preparedness for handling attacks for physical thre...
Table 8.6 Physical threats corpus of assessments.
Table 8.7 Levels of system’s preparedness for handling attacks for medical threa...
Table 8.8 Medical threats corpus of assessments.
Table 8.9 Levels of system’s preparedness for handling attacks exceptional situa...
Table 8.10 Exceptional situation caused attacks & threats - corpus of assessment...
Table 8.11 Points division for HMSB section.
Table 8.12 Results of cyber attacks & threats from its corpus of assessments.
Table 8.13 Results of physical threats from its corpus of assessments.
Table 8.14 Results of exceptional threats from its corpus of assessments.
Table 8.15 Results of medical threats from its corpus of assessments.
Table 8.16 Results of cyber attacks & threats from its corpus of assessments.
Table 8.17 Results of physical threats from its corpus of assessments.
Table 8.18 Results of exceptional threats from its corpus of assessments.
Table 8.19 Results of medical threats from its corpus of assessments
Chapter 9
Table 9.1 IoT devices (source gartner).
Table 9.2 Types of trust.
Chapter 10
Table 10.1 Comparison of various face recognition approaches.
Table 10.2 Comparison of various forensic face recognition approaches.
Chapter 11
Table 11.1 Criminals and attackers usually perform malicious activity by using t...
Table 11.2 Different file system uses to analyze and recover the file [21].
Table 11.3 Details of different carving techniques [23, 24].
Table 11.4 Description of volatile data forensic toolkit [25].
Table 11.5 Description of non-volatile data forensic toolkit [26].
Chapter 12
Table 12.1 Distributing info.
Table 12.2 Classifiers’ success in recognizing various categories of feedback re...
Table 12.3 Classifiers’ success in pinpointing various categories of malwarerela...
Table 12.4 Classifier’s success for distinguishing various forms of malware rela...
Table 12.5 Classifiers’ success by defining various forms of malware related to ...
Table 12.6 Categories of dispersal of responses for fi ve businesses indicates t...
Table 12.7 The delivery category related to malware in fi ve businesses reveals ...
Chapter 13
Table 13.1 Comparison of key characteristics of various datasets.
Chapter 14
Table 14.1 Comparison of various studies carried out for detection of separate a...
Table 14.2 The use of smart contracts in various domains.
Table 14.3 The user-targeted in various industrial sectors.
Chapter 16
Table 16.1 Ransomware traits.
Guide
Cover
Table of Contents
Title Page
Copyright
Preface
Acknowledgment
Begin Reading
Index
Also of Interest
End User License Agreement
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