Search

Browse Subject Areas

For Authors

Submit a Proposal

Emerging Threats and Countermeasures in Cybersecurity

Edited by Gulshan Shrivastava, Rudra Pratap Ojha, Shashank Awasthi, Himani Bansal, and Kavita Sharma
Copyright: 2025   |   Expected Pub Date:2024//
ISBN: 9781394230570  |  Hardcover  |  
528 pages
Price: $225 USD
Add To Cart

One Line Description
This book is an essential resource for anyone seeking to stay ahead in the dynamic field of cybersecurity, providing a comprehensive toolkit for understanding and combating digital threats and offering practical, insightful guidance ideal for cybersecurity professionals, digital forensic investigators, legal practitioners, law enforcement, scholars, and students.

Audience
Cybersecurity professionals, law enforcement agencies, legal professionals, students and academics, business professionals, and government agencies interested in areas of computer science, cyber security, digital forensics, and information technology

Description
In the rapidly evolving domain of digital security, Emerging Threats and Countermeasures in Digital Forensics and Cybersecurity emerges as a vital guide for understanding and addressing the sophisticated landscape of cyber threats. This in depth volume, featuring contributions from renowned experts, provides a thorough examination of the current state and future challenges in digital security and forensic analysis. The book is meticulously organized into seven sections (excluding conclusion), each focusing on a critical aspect of cybersecurity. It begins with a comprehensive overview of the latest trends and threats in the field, setting the stage for deeper explorations in subsequent sections. Readers will gain insights into a range of topics, from the intricacies of advanced persistent threats and malware, to the security nuances of cyberphysical systems and the Internet of Things (IoT).

Of particular note is the books exploration of cutting-edge topics like blockchain and cryptographic technologies and a detailed analysis of social engineering tactics, cloud security, and data privacy. Each chapter blends theoretical frameworks with practical case studies, offering a balanced perspective that is both informative and applicable in real world scenarios. This book is more than just a compilation of research; it is a practical, insightful guide ideal for cybersecurity professionals, digital forensic investigators, legal practitioners, law enforcement, scholars, and students. It provides a comprehensive toolkit for understanding and combating digital threats, making it an essential resource for anyone seeking to stay ahead in the dynamic field of cybersecurity.

Back to Top
Author / Editor Details
Gulshan Shrivastava, PhD is an associate professor at the School of Computer Science Engineering and Technology at Bennett University, India. He has published five patents and over 55 articles, books, and editorials in international journals and conferences of high repute. He is a life member of the International Society for Technology in Education, senior member of the Institute of Electrical and Electronics Engineers, and professional member of many professional bodies.

Rudra Pratap Ojha, PhD is a professor in the Department of Computer Science and Engineering, G. L. Bajaj Institute of Technology and Management, India. He has published more than 15 papers in national and international journals and conferences. He also works as an editor in various reputed journals and has delivered expert talks and guest lectures at various prestigious institutes. Additionally, he is a life member of the Computer Society of India.

Shashank Awasthi, PhD is a professor in the Department of Computer Science and Engineering, G.L. Bajaj Institute of Technology and Management, India. He has more than 18 years of teaching and research experience across eight countries and has presented his research at various international conferences. He has published more than a dozen research papers in national and international journals of repute. He is a lifetime member of the Institute of Electrical and Electronics Engineers and International Association of Engineers, Hong Kong.

Himani Bansal, PhD is an assistant professor at the Jaypee Institute of Information Technology, Noida, India with over 14 years of experience in academia and the corporate sector. She has published many research papers in various international journals and conferences, as well as chapters and books in several international book series. Additionally, she has served as an editor for several journals and has organized, coordinated, and attended numerous trainings, seminars, and workshops.

Kavita Sharma, PhD is a professor in the Department of Computer Science and Engineering at the Galgotias College of Engineering & Technology, India. She has also been awarded a research fellowship from the Ministry of Electronics and Information Technology from the Government of India. She has more than 12 years of experience in academia and research. She has four patents and has published seven books and 45 research articles in international journals and conferences of high repute and has served as a guest editor, editorial board member, and member of an international advisory board. Additionally, she has actively participated and organized several international conferences, faculty development programs, and various national and international workshops and is a member of numerous professional organizations.

Back to Top

Table of Contents
Preface
1. Emerging Threats and Trends in Digital Forensics and Cybersecurity
Sethu Laksmi S., Lekshmi Das, Razil S.R. Khan and Pooja Chakraborty
1.1 Introduction
1.2 Threats Faced by Digital Forensics
1.2.1 Technical Challenges
1.2.2 Operational Challenges
1.2.3 Personnel-Related Challenges
1.3 Cybersecurity Threats in 2023
1.3.1 Social Engineering
1.3.2 Third-Party Exposure
1.3.3 Configuration Mistakes
1.3.4 Poor Cyber Hygiene
1.3.5 Cloud Vulnerabilities
1.3.6 Mobile Device Vulnerabilities
1.3.7 Internet of Things (IoT)
1.3.8 Ransomware
1.3.9 Poor Data Management
1.3.10 Inadequate Post-Attack Procedures
1.4 New Era of Technology and Their Risks
1.4.1 Autonomous Vehicles
1.4.2 Artificial Intelligence
1.4.3 Robotics and Robotics Process Automation
1.4.4 Internet of Things (IoT)
1.4.5 5G
1.5 Challenges for Digital Forensics
1.5.1 High Speed and Volumes
1.5.2 Explosion Complexity
1.5.3 Development of Standards
1.5.4 Privacy-Preserving Investigations
1.5.5 Legitimacy
1.5.6 Rise of Anti-Forensic Techniques
1.6 Impact of Mobile Gadgets on Cybersecurity
1.7 The Vulnerabilities in Wireless Mobile Data Exchange
1.7.1 Interception of Data
1.7.2 Malware Attacks
1.7.3 Rogue Access Points
1.7.4 Denial of Service Attacks
1.7.5 Weak Encryption
1.8 Network Segmentation and its Applications
1.8.1 Applications
1.8.2 Benefits of Network Segmentation
1.9 Relationship Between Privacy and Security
1.9.1 Security
1.9.2 Privacy
1.10 Recent Trends in Digital Forensics
1.10.1 Cloud Forensics
1.10.2 Social Media Forensics
1.10.3 IoT Forensics
1.11 Opportunities in this Field
1.11.1 USB Forensics
1.11.2 Intrusion Detection
1.11.3 Artificial Intelligence (AI)
1.12 Future Enhancements in Digital Forensics
1.13 Cybersecurity and Cyber Forensics in Smart Cities
1.13.1 Smart Cities are Entitled to Cyber-Physical Systems
1.13.1.1 Administrative
1.13.1.2 Complex CPS in a Glimpse
1.13.1.3 IoT Technologies in Smart Cities of the Future
1.14 Network Security and Forensics
1.15 Software and Social Engineering Attacks on RSA
1.16 Cyber Threats and Cybersecurity
1.17 Conclusion
Bibliography
2. Toward Reliable Image Forensics: Deep Learning-Based Forgery Detection
Choudhary Shyam Prakash, Sahani Pooja Jaiprakash and Naween Kumar
2.1 Introduction
2.2 Fundamentals of Image Forensics
2.2.1 History
2.2.2 Image Forgery Types
2.2.3 Classical Image Forensics Techniques
2.3 Deep Learning in Image Forensics
2.3.1 Convolutional Neural Networks (CNNs)
2.3.2 Generative Adversarial Networks (GANs)
2.4 Datasets of Image Forgery Detection
2.5 Feature Extraction and Representation
2.6 Model Training and Evaluation
2.6.1 Model Training
2.6.2 Loss Functions
2.6.3 Evaluation Metrics
2.7 Challenges and Future Scope
2.8 Conclusion
References
3. Understanding and Mitigating Advanced Persistent Threats in a Dynamic
Cyber Landscape
Shami Sushant and Shipra Rohatgi
3.1 Introduction
3.1.1 Advanced
3.1.2 Persistent
3.1.3 Threat
3.1.3.1 Vulnerability
3.1.3.2 Risk
3.2 APT Lifecycle
3.3 Characteristics and Methods of APTs
3.4 APT Detection
3.5 Mitigation Techniques
3.5.1 Application Control/Dynamic Whitelisting
3.5.2 Vulnerability Assessment
3.5.3 Patch Management
3.5.4 Automated Exploit Prevention
3.6 Case Study: CozyDuke APT
Conclusion
References
4. Class-Imbalanced Problems in Malware Analysis and Detection in Classification Algorithms
Bidyapati Thiyam, Chadalavada Suptha Saranya and Shouvik Dey
4.1 Introduction
4.2 Background
4.2.1 Malware Analysis and Types
4.2.2 Class-Imbalanced Problem
4.2.3 Imbalanced Techniques
4.3 Related Work
4.4 Detailed Overview of the Methodology
4.4.1 Dataset Information
4.4.2 Different Evaluation Metrics Used for Class-Imbalanced Study
4.4.3 Machine Learning Classifiers
4.4.4 Exiting Methods Used for Handling the Class Imbalanced
4.5 Discussion and Challenges
4.5.1 Research Question
4.5.2 Challenges
4.6 Conclusion
References
5. Malware Analysis and Detection: New Approaches and Techniques
Laiba Mazhar and Shipra Rohatgi
5.1 Introduction
5.2 Malware
5.2.1 History of Malware
5.2.2 Different Forms of Malware
5.2.3 Purpose of Malware Analysis
5.3 Conclusion
References
6. State-of-the-Art in Ransomware Analysis and Detection
Amit Kumar Upadhyay, Preeti Dubey, Sahil Gandhi and Shreya Jain
6.1 Introduction
Evolution
Lifecycle
Infection Method
Targets of Ransomware Attacks
Payment Process and Method
Ransomware Analysis
Ransomware Detection
Ransomware Prevention
Recovery
Characteristics
Difficulties
Impact of Ransomware Attacks
Statistics
Conclusion
References
7. Cyber-Physical System Security: Challenges and Countermeasures
Ankit Garg, Anuj Kumar Singh, Aleem Ali and Madan Lal Saini
7.1 Introduction
7.1.1 Definition and Characteristics of CPS
7.1.2 Importance and Applications of CPS
7.1.3 Overview of CPS Security Concerns
7.2 Challenges in CPS Security
7.2.1 Threat Landscape in CPS
7.2.2 Vulnerabilities in CPS
7.2.2.1 Interconnected System Vulnerabilities
7.2.2.2 Lack of Standardized Security Frameworks
7.2.2.3 Legacy System Compatibility Issues
7.2.2.4 Human Factors and Social Engineering
7.3 Security Risks and Consequences
7.3.1 Financial Losses and Economic Impact
7.3.2 Public Safety and Critical Infrastructure Risks
7.3.3 Privacy and Data Breaches
7.4 Key Considerations for CPS Security
7.4.1 Secure Design and Architecture Principles
7.4.1.1 Defense-in-Depth Strategy
7.4.1.2 Secure Communication Protocols
7.4.1.3 Access Control and Authentication Mechanisms
7.4.2 Threat Modeling and Risk Assessment
7.4.3 Intrusion Detection and Prevention Systems (IDPS)
7.4.4 Secure Software Development Practices
7.4.4.1 Secure Coding Guidelines
7.4.4.2 Code Reviews and Vulnerability Testing
7.5 Countermeasures for CPS Security
7.5.1 Network Security Measures
7.5.1.1 Firewalls and Network Segmentation
7.5.1.2 IDPS
7.5.2 Physical Security Controls
7.5.2.1 Access Controls and Physical Barriers
7.5.2.2 Surveillance and Monitoring Systems
7.5.3 Incident Response and Recovery Plans
7.5.3.1 Incident Handling Procedures
7.5.3.2 Backup and Disaster Recovery Strategies
7.5.4 Security Awareness and Training Programs
7.6 Case Studies and Examples
7.6.1 Case Study 1: Industrial Control System (ICS) Security
7.6.1.1 Countermeasures
7.6.2 Case Study 2: Smart Cities and Infrastructure Protection
7.6.2.1 Countermeasures
7.6.3 Case Study 3: Autonomous Vehicles and Transportation Systems
7.6.3.1 Countermeasures
7.7 Future Directions and Emerging Technologies
7.7.1 Impact of Emerging Technologies on CPS Security
7.7.2 Challenges and Opportunities in Securing CPS in the Future
7.8 Conclusion
References
8. Unraveling the Ethical Conundrum: Privacy Challenges in the Realm of Digital Forensics
Tushar Krishnamani and Parmila Dhiman
8.1 Introduction
8.2 Fundamental Concepts in Digital Forensics
8.3 Privacy Concerns in AI Technology: Security Systems and Cyber Forensics
8.4 Maintaining Integrity of Evidence in Forensic Investigations
8.5 Ethical Obligations of Forensic Investigators
8.6 Conclusion
References
9. IoT and Smart Device Security: Emerging Threats and Countermeasures
Akhilesh Kumar Singh, Ajeet Kumar Sharma, Surabhi Kesarwani, Pradeep Kumar Singh, Pawan Kumar Verma and Seshathiri Dhanasekaran
9.1 Introduction
9.2 The Growth of IoT and Smart Devices
9.3 Emerging Threat Landscape
9.4 Device Vulnerabilities and Exploits
9.5 Data Privacy and Leakage
9.5.1 Data Privacy Concerns in IoT
9.5.2 Data Leakage Concerns in IoT
9.6 Network Attacks and Amplification
9.6.1 Network Attacks in IoT
9.6.2 Amplification Attacks in IoT
9.6.3 Preventive Measures and Mitigation
9.7 Physical Attacks on Smart Devices
9.8 Supply Chain Risks in IoT Ecosystem
9.9 Lack of Standardization in IoT Security
9.10 Countermeasures and Best Practices
9.11 Conclusion and Future Directions
9.11.1 Future Directions and Countermeasures
References
10. Advanced Security for IoT and Smart Devices: Addressing Modern Threats
and Solutions
Himanshu Sharma, Prabhat Kumar and Kavita Sharma
10.1 Introduction
10.1.1 Overview of IoT and Smart Devices
10.1.2 Importance of Security in IoT and Smart Devices
10.1.3 Scope of the Chapter
10.2 IoT and Smart Device Landscape
10.2.1 Growth and Adoption of IoT and Smart Devices
10.2.2 Types and Examples of IoT and Smart Devices
10.2.3 Challenges in Securing IoT and Smart Devices
10.3 Emerging Threats in IoT and Smart Device Security
10.3.1 Malware and Ransomware Attacks
10.3.2 Device Exploitation and Hijacking
10.3.3 Data Breaches and Privacy Concerns
10.3.4 Distributed Denial of Service (DDoS) Attacks
10.3.5 Supply Chain Attacks
10.3.6 Insider Threats
10.3.7 Physical Security Risks
10.4 Vulnerabilities in IoT and Smart Devices
10.4.1 Insecure Communication Protocols
10.4.2 Weak Authentication and Authorization
10.4.3 Lack of Security Updates and Patch Management
10.4.4 Default or Hardcoded Credentials
10.4.5 Lack of Device Integrity Verification
10.4.6 Insufficient Encryption
10.4.7 Inadequate Access Controls
10.5 Countermeasures and Best Practices
10.5.1 Secure Device Design and Development
10.5.2 Robust Authentication and Access Controls
10.5.3 Encryption and Secure Communication Protocols
10.5.4 Regular Security Updates and Patch Management
10.5.5 Device Monitoring and Anomaly Detection
10.5.6 User Education and Awareness
10.5.7 Network Segmentation and Isolation
10.6 Security Standards and Regulations
10.6.1 Industry Standards for IoT and Smart Device Security
10.6.2 Regulatory Landscape for IoT and Smart Devices
10.6.3 Compliance and Certification Programs
10.7 Security Testing and Assessment
10.7.1 Penetration Testing and Vulnerability Assessments
10.7.2 Code and Firmware Analysis
10.7.3 Network Monitoring and Intrusion Detection
10.7.4 Security Audits and Compliance Assessments
10.8 Incident Response and Recovery
10.8.1 Incident Detection and Response Planning
10.8.2 Data Backup and Recovery Strategies
10.8.3 Incident Investigation and Forensics
10.8.4 Communication and Public Relations
10.9 Case Studies: Real-World Examples
10.9.1 Notable IoT and Smart Device Security Breaches
10.9.1.1 Mirai Botnet Attack
10.9.1.2 Stuxnet Attack
10.9.1.3 Jeep Cherokee Hack
10.9.1.4 Equifax Data Breach
10.9.2 Lessons Learned and Mitigation Strategies
10.9.2.1 Strong Authentication and Access Controls
10.9.2.2 Regular Security Updates and Patch Management
10.9.2.3 Network Segmentation and Isolation
10.9.2.4 Threat Intelligence and Monitoring
10.9.2.5 User Education and Awareness
10.9.2.6 Security by Design
10.9.2.7 Collaboration and Information Sharing
10.10 Future Trends and Challenges
10.10.1 AI and Machine Learning in IoT Security
10.10.2 Edge Computing and Security Implications
10.10.3 Blockchain and Distributed Ledger Technology
10.10.4 Quantum Computing and Its Impact on Security
10.11 Conclusion
References
11. Threats and Countermeasures for IoT and Smart Devices
Amrit Suman, Preetam Suman, Sasmita Padhy, Roshan Jahan and Naween Kumar
11.1 Introduction
11.2 IoT Architecture
11.2.1 Perception Layer
11.2.2 Network Layer
11.2.3 Application Layer
11.2.4 The Transport Layer
11.2.5 The Processing Layer
11.2.6 The Business Layer
11.3 Security in the Application Layer of IoT
11.3.1 Messaging Protocols
11.3.1.1 MQTT “Message Queuing Telemetry Transport Protocol”
11.3.1.2 Constrained-Application Protocol (CoAp)
11.3.1.3 AMQP “Advanced Message Queuing Protocol”
11.3.1.4 Data Distribution Service (DDS)
11.3.1.5 Extensible Messaging Protocol (XMPP)
11.3.2 Service Protocols
11.3.2.1 Multicast Domain Name System (mDNS)
11.3.2.2 Simple Service Discovery Protocol (SSDP)
11.4 Literature Survey
11.4.1 Countermeasures and IoT Threat-Mitigation Techniques
11.5 Results and Discussion
11.6 Conclusion and Future Work
References
12. Insider Threat Detection and Prevention: New Approaches and Tools
Rakhi S., Sampada H. K., Arun Balodi, Shobha P. C. and Roshan Kumar
12.1 Introduction
12.2 Insider Attack: A Big Picture
12.3 Tools and Technology for Insider Threat Detection
12.3.1 User and Entity Behavior Analytics (UEBA) Platforms
12.3.2 Data Loss Prevention (DLP) Solutions
12.3.3 Endpoint Detection and Response (EDR) Platforms
12.3.4 Security Information and Event Management (SIEM) Systems
12.3.5 User Activity Monitoring (UAM) Solutions
12.3.6 Insider Threat Intelligence Platforms
12.3.7 Privileged Access Management (PAM) Solutions
12.3.8 Machine Learning and AI-Based Tools
12.3.9 Insider Threat Mitigation in Cloud Environments
12.3.10 Psychological and Behavioral Aspects
12.4 Results and Discussions
12.5 Conclusion
References
13. A Holistic Framework for Insider Threat Detection and Analysis Upon Security and Privacy for Data Management Services
A. Sheik Abdullah, Hanish Shyam, Sriram B., Arif Ansari and Subramanian Selvakumar
13.1 Introduction
13.1.1 Need for a Holistic Framework for Data Management Services
13.1.2 Problem Statement
13.1.3 Challenges in Developing a Holistic Framework for DMS
13.1.4 Characteristics of Effective Framework for DMS
13.1.5 Assumptions
13.2 Defining Insider Threats
13.2.1 Types of Insider Threats Targeting DMS
13.2.2 Precursor and Indicators
13.2.3 Expression of Insider Attacks
13.2.4 Incentives for Insider Attack
13.3 Know Your Critical Assets in Data Management Services
13.3.1 Identifying Assets in DMS
13.3.2 Data Classification and Segmentation
13.3.3 Challenges to Asset Identification
13.4 Insider Risk Management
13.4.1 Modern Risk Pain Points
13.4.2 Plan for Insider Risk Management
13.4.3 Conducting Risk Assessment
13.4.4 Risk Levels with Acceptance Criteria
13.4.5 Prioritization of Risk
13.5 Diving Deeper Into Holistic Framework
13.5.1 Administration and its Scope
13.5.1.1 Approaches and Tools
13.5.2 Technical and its Scope
13.5.2.1 Approaches and Tools
13.5.3 Physical and Its Scope
13.5.3.1 Approaches and Tools
13.6 Conclusion
References
14. Revolutionizing SEO: Exploring the Synergy of Blockchain Technology and Search Ecosystems
Bharti Aggarwal, Dinesh Rai and Naresh Kumar
14.1 Introduction
14.2 Features of Blockchain
14.3 Literature Review
14.4 Integrating Blockchain into Search Ecosystems for Enhancing SEO
14.5 Integration of Blockchain in Search Ecosystems
14.6 Concept of Decentralized Search Platforms and Role in SEO Improvement
14.7 Use Cases and Projects Illustrating Blockchain Integration in Search Ecosystems
14.8 Future Trends and Implications
14.9 Potential Implications for the SEO Industry and Online Marketing Strategies
14.10 Conclusion
References
15. Emerging Trends and Future Directions of Blockchain Technology in Education
Urvashi Sugandh, Priyanka Gaba, Arvind Panwar and Jyoti Agarwal
15.1 Introduction
15.1.1 Background on the Current State of Blockchain Technology in Education
15.1.2 Importance of Exploring Emerging Trends and Future Directions
15.1.3 Purpose of the Chapter
15.2 Overview of Blockchain Technology in Education
15.2.1 Review of Blockchain Technology’s Basics
15.2.2 Blockchain’s Current Uses in Education
15.2.3 The Value of Staying Current With Emerging Trends
15.3 Emerging Trends in Blockchain and Education
15.3.1 Lifelong Learning and Blockchain-Based Digital Credentials
15.3.2 Competency-Based Education and Blockchain
15.3.3 Learning Analytics and Blockchain
15.3.4 Learning Platforms and Marketplaces Driven by Blockchain
15.4 Implications for the Future of Education
15.4.1 Advancements in Blockchain Technology and Their Potential Impact
15.4.2 Benefits and Challenges of Adopting Emerging Blockchain Trends
15.4.3 Opportunities for Educational Institutions and Stakeholders
15.5 Future Directions for Blockchain in Education
15.5.1 Research Directions and Areas for Further Exploration
15.5.2 Integration of Emerging Technologies With Blockchain in Education
15.5.3 Scalability, Interoperability, and Standardization Challenges to Address
15.6 Conclusion
15.6.1 Overview of Important Emerging Trends and Their Consequences
15.6.2 Analysis of Blockchain’s Future Potential in Education
15.6.3 Final Thoughts on the Value of Adopting Emerging Trends and Directions
References
16. Social Engineering Attacks: Detection and Prevention
Manpreet Kaur Aiden, Sonia Chhabra, Shweta Mayor Sabharwal and Alaa Ali Hameed
16.1 Introduction
16.2 Phases of Social Engineering
16.2.1 Preparation
16.2.2 Choose a Target
16.2.3 Build a Relation
16.2.4 Manipulate a Relation
16.3 Methods of Social Engineering
16.3.1 Human-Centric Social Engineering
16.3.1.1 Impersonation
16.3.1.2 Eavesdropping
16.3.1.3 Shoulder Surfing
16.3.1.4 Dumpster Diving
16.3.1.5 Reverse Social Engineering
16.3.1.6 Piggybacking
16.3.1.7 Tailgating
16.3.1.8 Diversion Theft
16.3.1.9 Honey Trap
16.3.1.10 Baiting
16.3.1.11 Quid Pro Quo
16.3.1.12 Elicitation
16.3.2 Computer-Centric Social Engineering
16.3.2.1 Pop-Up Windows
16.3.2.2 Hoax Letters
16.3.2.3 Chain Letters
16.3.2.4 Instant Chat Messenger
16.3.2.5 Spam Email
16.3.2.6 Scareware
16.3.2.7 Phishing
16.3.3 Mobile-Centric Social Engineering
16.3.3.1 Publish Malicious Apps
16.3.3.2 Repackage Legitimate Apps
16.3.3.3 Untrusted Security Applications
16.3.3.4 SMS Phishing
16.4 Insider Threat
16.4.1 Types of Insider Threat
16.4.1.1 Privileged Users
16.4.1.2 Disgruntled Workers
16.4.1.3 Accident-Prone Employees
16.4.1.4 Undertrained Staff
16.4.1.5 Third Parties
16.4.2 Reasons for Insider Attacks
16.4.2.1 Financial Motivation
16.4.2.2 Theft of Confidential Data
16.4.2.3 Revenge
16.4.2.4 Future Competition
16.4.2.5 Performing Competitors’ Bidding
16.4.2.6 Public Impact
16.4.3 Insider Threat Statistics
16.4.4 Insider Threats Types
16.4.4.1 Malicious Insider
16.4.4.2 Negligent Insider
16.4.4.3 Professional Insider
16.4.4.4 Compromised Insider
16.4.4.5 Accidental Insider
16.5 Impersonation on Social Media Platforms
16.5.1 Social Engineering for Social Media Platforms
16.5.1.1 By Creating a False Profile
16.5.1.2 By Unauthorized Access
16.5.2 Impersonation on Facebook
16.6 Identity Theft
16.6.1 Different Types of Identity Theft
16.6.1.1 Child Identity Theft
16.6.1.2 Hacker Identity Theft
16.6.1.3 Monetary Identity Theft
16.6.1.4 Driver’s License Identity Theft
16.6.1.5 Policy Identity Theft
16.6.1.6 Healthcare Identity Theft
16.6.1.7 Tax Identity Theft
16.6.1.8 Identity Replication and Disguise
16.6.1.9 Artificial Identity Theft
16.6.1.10 Social Identity Theft
16.6.2 Methods Employed by Attackers to Steal Identities
16.6.2.1 Loss of Personal Items
16.6.2.2 Internet Searches
16.6.2.3 Social Engineering
16.6.2.4 Dumpster Diving and Shoulder Surfing
16.6.2.5 Phishing
16.6.2.6 Skimming
16.6.2.7 Pretexting
16.6.2.8 Pharming
16.6.2.9 Hacking (Compromising a User’s System)
16.6.2.10 Keyloggers and Password Stealers (Malware)
16.6.2.11 Wardriving
16.6.2.12 Mail Theft and Rerouting
16.7 Social Engineering Detection and Prevention
16.7.1 Preventing Social Engineering
16.7.1.1 Password Policies
16.7.1.2 Physical Security Policies
16.7.1.3 Defense Strategy
16.7.2 How to Defend Against Phishing Attacks?
16.7.3 Detecting Insider Threats
16.7.3.1 Insider Risk Controls
16.7.3.2 Deterrence Controls
16.7.3.3 Data Loss Prevention (DLP) and Identity and Access Management (IAM)
16.7.3.4 Detection Controls
16.7.4 Insider Threat Countermeasures
16.7.4.1 Segregation and Rotation of Responsibilities
16.7.4.2 Least Privileges
16.7.4.3 Controlled Access
16.7.4.4 Logging and Auditing
16.7.4.5 Employee Monitoring
16.7.4.6 Legal Policies
16.7.4.7 Archive Critical Data
16.7.4.8 Employee Cybersecurity Training
16.7.4.9 Employee Background Verification
16.7.4.10 Periodic Risk Assessment
16.7.4.11 User Privilege Monitoring
16.7.4.12 Credentials Deactivation for Terminated Employees
16.7.4.13 Regular Risk Evaluation
16.7.4.14 Layered Defense
16.7.4.15 Physical Security
16.7.4.16 Surveillance
16.7.4.17 Zero-Trust Model
16.7.4.18 Behavioral Analytics
16.7.5 Identity Theft Prevention
16.7.5.1 Ensure Your Name is Not on Marketing Lists
16.7.5.2 Securely Store or Shred Private Information Documents
16.7.5.3 Safeguard Credit Card Statements
16.7.5.4 Avoid Providing Sensitive Information via Phone
16.7.5.5 Retrieve Mail Promptly
16.7.5.6 Be Cautious of Personal Information Requests
16.7.5.7 Monitor Online Banking Activities
16.7.5.8 Use Caution When Sharing Personal Information Online
16.7.5.9 Implement Two-Step Verification
16.7.6 Suspicious Email Detection
16.7.6.1 Generic Greetings from Banks, Businesses, or Social Networking Sites
16.7.6.2 Emails from People in Your Address Book
16.7.6.3 Urgent Tones or Veiled Threats, Grammar or Spelling Errors
16.7.6.4 Links to Fake Websites, Offers Too Good to be True
16.7.6.5 Official-Looking Logos and Details from Reliable Sources
16.7.7 Anti-Phishing Toolbar
16.7.7.1 Netcraft Source
16.7.7.2 Phish Tank Source
16.7.8 Social Engineering: Targets and Prevention
16.7.9 Social Engineering Tools
16.8 Conclusion and Future Directions
References
17. Social Engineering Attacks in Industrial Internet of Things and Smart Industry: Detection and Prevention
Muhammad Muzamil Aslam, Kassim Kalinaki, Ali Tufail, Abdul Ghani Haji Naim, Madiha Zahir Khan and Sajid Ali
17.1 Introduction
17.2 Phases of Social Engineering Attacks
17.2.1 Discovery and Investigation
17.2.2 Deception and Hook
17.2.3 Attack
17.2.4 Retreat
17.3 Social Engineering Attacks in IoT and IIoT
17.4 Techniques of Social Engineering Attacks
17.4.1 Phishing
17.4.2 Angler Phishing
17.4.3 Business Email Compromise (BEC)
17.4.4 Pharming
17.4.5 Spear Phishing
17.4.6 Tabnabbing
17.4.7 Whaling
17.4.8 Baiting
17.4.9 Scareware
17.4.10 Diversion Theft
17.4.11 SMS Phishing
17.4.12 Pretexting
17.4.13 Quid Pro Quo
17.4.14 Tailgating
17.4.15 Voice Phishing/Vishing
17.4.16 Watering Hole
17.4.17 Advance Fee Scam
17.5 Social Engineering Attack Vectors
17.5.1 Compromised Email
17.5.2 Weak Credentials
17.5.3 Malicious Insider
17.5.4 Careless Insider
17.5.5 A Mole
17.5.6 Misconfiguration
17.5.7 Phishing
17.5.8 Ransomware
17.6 Social Engineering Attack Detection and Prevention Techniques
17.6.1 Security Awareness Training
17.6.2 Endpoint and Antivirus Security Tools
17.6.3 Penetration Testing
17.6.4 Build a Positive Security Culture
17.6.5 Implement Advanced Security Measures in the Industry
17.7 Real-World Social Engineering Attacks in the Industry
17.7.1 Carbanak Fraud
17.7.2 Fax Notice Scam
17.7.3 Dropbox
17.7.4 Deepfake Attack on UK Energy Company
17.7.5 The Sacramento Phishing Attack Exposes Health Information
17.8 Challenges and Future Prospective in Social Engineering Attacks
17.9 Future Prospective and Recommendations
17.10 Conclusion
References
18. Cloud Security Essentials: A Detailed Exploration
Abhishek Singh Vardia, Aarti Chaudhary, Shikha Agarwal, Anil Kumar Sagar and Gulshan Shrivastava
18.1 Introduction
18.2 The Importance of Cloud Security
18.2.1 Data Protection
18.2.2 Business Continuity
18.2.3 Compliance and Regulation
18.3 Key Cloud Security Concerns
18.3.1 Data Exploits
18.3.2 Insecure APIs
18.3.3 Compliance and Legal Issues
18.3.4 Insider Threats
18.3.5 Shared Responsibility Model
18.3.6 Vendor Lock-In
18.3.7 Lack of Transparency
18.3.8 Emerging Threats and Evolving Security
18.3.9 Network Security
18.3.10 Identity and Access Management (IAM)
18.3.11 Cloud-Shared Technology Risks
18.3.12 Cloud Compliance and Auditing
18.3.13 Data Encryption
18.3.14 Cloud-Based Applications
18.3.15 DevOps and Continuous Integration/Continuous Deployment (CI/CD)
18.4 Cloud Security Challenges
18.4.1 Data Security and Privacy Concerns
18.4.2 Identity and Access Management (IAM)
18.4.3 Network Security Challenges
18.4.4 Evolving Threat Landscape
18.4.5 Vendor Lock-In
18.4.6 Lack of Cloud Security Expertise
18.5 Cloud Security Challenges and Strategies
18.6 Common Threats in Cloud Security
18.6.1 Unauthorized Access
18.6.2 Data Breaches
18.6.3 DDoS Attacks
18.7 Best Practices for Cloud Security
18.7.1 Data Security
18.7.2 Identity and Access Management (IAM)
18.7.3 Network Security
18.7.4 Adaptation to Threats
18.7.5 Vendor Lock-In Mitigation
18.7.6 Human Element in Security
18.8 Conclusion
References
19. Data Privacy and Protection: Legal and Ethical Challenges
Oladri Renuka, Niranchana RadhaKrishnan, Bodapatla Sindhu Priya, Avula Jhansy and Soundarajan Ezekiel
19.1 Introduction
19.2 Fundamental Concepts of Data Privacy and Protection
19.2.1 Data Privacy and Protection
19.2.2 Importance of Personal Data in the Digital Age
19.2.3 Relationship Between Privacy and Data Protection
19.2.3.1 Privacy as an Individual Right
19.2.3.2 Data Protection as Organizational Responsibility
19.2.3.3 The Symbiotic Balance
19.2.3.4 Navigating the Digital Landscape
19.3 Legal Frameworks for Data Privacy and Protection: Overview of Global Data Protection Laws
19.3.1 Comparative Analysis of Jurisdictional Approaches
19.4 Rights and Principles Underpinning Data Privacy
19.4.1 Right to Privacy as a Human Right
19.4.2 Consent and Its Function in Data Processing
19.4.3 Data Minimization, Purpose Limitation, and Accountability
19.5 Challenges in Implementing Data Privacy Regulations
19.5.1 Challenges for Businesses and Organizations
19.5.2 Balancing Operational Efficiency and Compliance
19.5.3 Navigating Cross-Border Data Transfers
19.6 Ethical Considerations in Data Collection and Usage: Transparency and Informed Consent
19.6.1 Transparency: Fostering Trust Through Openness
19.6.2 Minimizing Algorithmic Bias: Preserving Fairness and Equality
19.6.3 Ethical Responsibilities of Data Controllers and Processors
19.7 Emerging Technologies and Ethical Dilemmas: Impact of AI, IoT, and Biometrics on Data Privacy
19.7.1 Impact of AI, IoT, and Biometrics on Data Privacy
19.7.1.1 Impact of AI on Data Privacy: Balancing Innovation and Privacy
19.7.1.2 Impact of IoT on Data Privacy: Security and Consent Challenges
19.7.1.3 Biometrics’ Effect on Data Privacy: Juggling Privacy and Convenience
19.7.2 Ethical Challenges in Data Analytics and Profiling: Balancing Insight and Privacy
19.7.2.1 Privacy-Preserving Techniques and Solutions: Balancing Utility and Confidentiality
19.8 Legal and Ethical Reactions to Data Breach and Privacy Incidents: Legal
Requirements for Notifying Data Breach
19.8.1 Legal Obligations in Data Breach Notification: Ensuring Transparency and Accountability
19.8.1.1 Balancing Legal Obligations with Ethical Considerations
19.8.2 Ethical Handling of Data Breach Fallout: Mitigating Harm and Restoring Trust
19.8.3 Case Studies: Lessons From High-Profile Data Breaches
19.9 Surveillance, National Security, and Individual Privacy: Striking a Balance:
Privacy vs. National Security
19.9.1 Striking a Balance: Privacy vs. National Security
19.9.2 Ethics of Mass Surveillance and Data Retention: Balancing Security and Privacy
19.9.3 Maintaining Civil Rights in the Digital Age: Finding the Moral Middle Ground
19.10 Regulatory Enforcement and Accountability: Role of Data Protection Authorities
19.10.1 Role of Data Protection Authorities: Guardians of Data Privacy
19.10.1.1 Impact of Data Protection Authorities
19.10.2 Penalties, Fines, and Recourse for Non-Compliance: Dissuading Infractions
19.10.3 Corporate Social Responsibility in Data Protection: Ethical and Social Commitments
19.11 Future Trends and Considerations: Evolving Legal Landscapes and Global
Harmonization
19.11.1 Evolving Legal Landscapes: Adapting to Technological Change
19.11.1.1 Global Harmonization: Navigating Cross-Border Data Flow
19.11.2 Ethical Standards for Innovation Driven by Data: Handling the Complexity of Ethics
19.11.3 The Role of Education and Public Awareness: Empowering Informed Choices
19.12 Conclusion: Navigating the Nexus of Data Privacy and Protection
19.12.1 Synthesis of Legal and Ethical Challenges Explored
19.12.2 Call for Collaborative Efforts in Data Privacy and Protection
19.12.3 Ensuring a Balanced and Responsible Data Ecosystem
Conclusion
References
20. Future Direction in Digital Forensics and Cyber Security
Ar. Varsha, Nayana Anoop Kumar, Sosthenes Nyabuto Bichanga and Pooja Chakraborty
20.1 Introduction
20.2 Evolution of Crime
20.3 Existing Cybercrime Rate in India and World
20.3.1 Cybercrimes in India
20.3.1.1 Case Studies—Cybercrime in India
20.3.2 Cybercrime Worldwide—An Overview
20.3.2.1 Case Studies—Cybercrime Worldwide
20.4 Emerging Cybercrime and its Future
20.4.1 Internet of Things (IoT) Attacks
20.4.1.1 Case Study: Mirai Botnet
20.4.1.2 Prevention from the Internet of Things Attacks
20.4.1.3 Future of the Internet of Things Attacks
20.4.2 Audio Cloning
20.4.2.1 Consequences of Audio Cloning Artificial Intelligence
20.4.2.2 Future of AI Voice Cloning
20.4.3 Cryptocurrency Scams
20.4.3.1 Case Study: Ronin Network Crypto Heist
20.4.3.2 Prevention from Cryptocurrency Scams/Crypto Jacking
20.4.4 Cyberterrorism
20.4.4.1 Reasons for the Predominance of Cyberterrorism
20.4.5 Social Media Forensics
20.4.5.1 What is Social Media?
20.4.5.2 Understanding Social Media
20.4.5.3 Major Platforms of Social Media
20.4.5.4 What does Social Media Contain?
20.4.5.5 Nature of Social Media Crime
20.4.5.6 Examples of Social Media Crimes
20.4.5.7 Use of Social Media in Forensic Investigation
20.4.5.8 Tools for Detecting and Investigating Crime on Social Media
20.4.5.9 How can Fraud be Detected Using Social Media
20.5 Recent Paradigm Shift in Cyber Menace
20.5.1 Online Game: A New Approach to Cybercrime
20.5.1.1 Crimes Committed Through Online Gaming
20.5.1.2 Prevention from Online Gaming Crimes
20.5.2 Dark Web
20.5.2.1 Future of the Dark Web
20.5.2.2 Prevention from the Dark Web
20.6 Cyber Security
20.6.1 Future of Cyber Security
20.6.2 Threats of Future Cyber Security
20.7 Artificial Intelligence
20.7.1 Limitations of Artificial Intelligence
20.7.2 Threats of Artificial Intelligence in the Future
20.7.2.1 Deep Fake Attack
20.7.2.2 AI Phishing Attack
20.7.2.3 DoS Attack
20.7.2.4 Advanced Persistent Threat
20.7.2.5 Data Processing Giant
20.8 Contemporary Condition of Digital Forensics
20.9 Challenges of Digital Forensics
20.10 Legal Aspect of Cyber Laws
20.11 Prevention Against Cybercrimes
20.12 Conclusion
References
Index

Back to Top



Description
Author/Editor Details
Table of Contents
Bookmark this page