Emerging Threats and Countermeasures in Cybersecurity

Preface xxv 1 Emerging Threats and Trends in Digital Forensics and Cybersecurity 1 Sethu Laksmi S., Lekshmi Das, Razil S.R. Khan and Pooja Chakraborty 1.1 Introduction 1 1.2 Threats Faced by Digital Forensics 2 1.2.1 Technical Challenges 2 1.2.2 Operational Challenges 3 1.2.3 Personnel-Related Challenges 3 1.3 Cybersecurity Threats in 2023 3 1.3.1 Social Engineering 3 1.3.2 Third-Party Exposure 4 1.3.3 Configuration Mistakes 4 1.3.4 Poor Cyber Hygiene 4 1.3.5 Cloud Vulnerabilities 4 1.3.6 Mobile Device Vulnerabilities 5 1.3.7 Internet of Things (IoT) 5 1.3.8 Ransomware 5 1.3.9 Poor Data Management 5 1.3.10 Inadequate Post-Attack Procedures 5 1.4 New Era of Technology and Their Risks 6 1.4.1 Autonomous Vehicles 6 1.4.2 Artificial Intelligence 6 1.4.3 Robotics and Robotics Process Automation 6 1.4.4 Internet of Things (IoT) 6 1.4.5 5g 6 1.5 Challenges for Digital Forensics 7 1.5.1 High Speed and Volumes 7 1.5.2 Explosion Complexity 7 1.5.3 Development of Standards 7 1.5.4 Privacy-Preserving Investigations 7 1.5.5 Legitimacy 7 1.5.6 Rise of Anti-Forensic Techniques 8 1.6 Impact of Mobile Gadgets on Cybersecurity 8 1.7 The Vulnerabilities in Wireless Mobile Data Exchange 8 1.7.1 Interception of Data 8 1.7.2 Malware Attacks 9 1.7.3 Rogue Access Points 9 1.7.4 Denial of Service Attacks 9 1.7.5 Weak Encryption 9 1.8 Network Segmentation and its Applications 9 1.8.1 Applications 10 1.8.2 Benefits of Network Segmentation 10 1.9 Relationship Between Privacy and Security 10 1.9.1 Security 10 1.9.2 Privacy 10 1.10 Recent Trends in Digital Forensics 10 1.10.1 Cloud Forensics 11 1.10.2 Social Media Forensics 11 1.10.3 IoT Forensics 12 1.11 Opportunities in this Field 12 1.11.1 USB Forensics 12 1.11.2 Intrusion Detection 13 1.11.3 Artificial Intelligence (AI) 13 1.12 Future Enhancements in Digital Forensics 14 1.13 Cybersecurity and Cyber Forensics in Smart Cities 14 1.13.1 Smart Cities are Entitled to Cyber-Physical Systems 15 1.13.1.1 Administrative 15 1.13.1.2 Complex CPS in a Glimpse 16 1.13.1.3 IoT Technologies in Smart Cities of the Future 16 1.14 Network Security and Forensics 16 1.15 Software and Social Engineering Attacks on RSA 17 1.16 Cyber Threats and Cybersecurity 18 1.17 Conclusion 20 Bibliography 20 2 Toward Reliable Image Forensics: Deep Learning-Based Forgery Detection 23 Choudhary Shyam Prakash, Sahani Pooja Jaiprakash and Naween Kumar 2.1 Introduction 23 2.2 Fundamentals of Image Forensics 25 2.2.1 History 25 2.2.2 Image Forgery Types 26 2.2.3 Classical Image Forensics Techniques 26 2.3 Deep Learning in Image Forensics 27 2.3.1 Convolutional Neural Networks (CNNs) 28 2.3.2 Generative Adversarial Networks (GANs) 29 2.4 Datasets of Image Forgery Detection 31 2.5 Feature Extraction and Representation 32 2.6 Model Training and Evaluation 32 2.6.1 Model Training 32 2.6.2 Loss Functions 34 2.6.3 Evaluation Metrics 34 2.7 Challenges and Future Scope 35 2.8 Conclusion 36 References 36 3 Understanding and Mitigating Advanced Persistent Threats in a Dynamic Cyber Landscape 39 Shami Sushant and Shipra Rohatgi 3.1 Introduction 39 3.1.1 Advanced 40 3.1.2 Persistent 40 3.1.3 Threat 41 3.1.3.1 Vulnerability 41 3.1.3.2 Risk 41 3.2 APT Lifecycle 42 3.3 Characteristics and Methods of APTs 43 3.4 APT Detection 46 3.5 Mitigation Techniques 51 3.5.1 Application Control/Dynamic Whitelisting 51 3.5.2 Vulnerability Assessment 53 3.5.3 Patch Management 54 3.5.4 Automated Exploit Prevention 55 3.6 Case Study: CozyDuke APT 56 Conclusion 58 References 58 4 Class-Imbalanced Problems in Malware Analysis and Detection in Classification Algorithms 61 Bidyapati Thiyam, Chadalavada Suptha Saranya and Shouvik Dey 4.1 Introduction 61 4.2 Background 62 4.2.1 Malware Analysis and Types 62 4.2.2 Class-Imbalanced Problem 63 4.2.3 Imbalanced Techniques 63 4.3 Related Work 64 4.4 Detailed Overview of the Methodology 72 4.4.1 Dataset Information 72 4.4.2 Different Evaluation Metrics Used for Class-Imbalanced Study 73 4.4.3 Machine Learning Classifiers 74 4.4.4 Exiting Methods Used for Handling the Class Imbalanced 75 4.5 Discussion and Challenges 76 4.5.1 Research Question 76 4.5.2 Challenges 77 4.6 Conclusion 77 References 77 5 Malware Analysis and Detection: New Approaches and Techniques 83 Laiba Mazhar and Shipra Rohatgi 5.1 Introduction 83 5.2 Malware 84 5.2.1 History of Malware 85 5.2.2 Different Forms of Malware 85 5.2.3 Purpose of Malware Analysis 87 5.3 Case Studies 99 5.4 Future Aspects 102 5.5 Conclusion 107 References 108 6 State-of-the-Art in Ransomware Analysis and Detection 111 Amit Kumar Upadhyay, Preeti Dubey, Sahil Gandhi and Shreya Jain 6.1 Introduction 111 Evolution 113 Lifecycle 116 Infection Method 118 Targets of Ransomware Attacks 120 Payment Process and Method 121 Ransomware Analysis 122 Ransomware Detection 123 Ransomware Prevention 126 Recovery 128 Characteristics 130 Difficulties 131 Impact of Ransomware Attacks 132 Statistics 134 Conclusion 134 References 134 7 Cyber-Physical System Security: Challenges and Countermeasures 137 Ankit Garg, Anuj Kumar Singh, Aleem Ali and Madan Lal Saini 7.1 Introduction 137 7.1.1 Definition and Characteristics of CPS 138 7.1.2 Importance and Applications of CPS 140 7.1.3 Overview of CPS Security Concerns 140 7.2 Challenges in CPS Security 141 7.2.1 Threat Landscape in CPS 142 7.2.2 Vulnerabilities in CPS 142 7.2.2.1 Interconnected System Vulnerabilities 143 7.2.2.2 Lack of Standardized Security Frameworks 144 7.2.2.3 Legacy System Compatibility Issues 144 7.2.2.4 Human Factors and Social Engineering 145 7.3 Security Risks and Consequences 145 7.3.1 Financial Losses and Economic Impact 145 7.3.2 Public Safety and Critical Infrastructure Risks 146 7.3.3 Privacy and Data Breaches 147 7.4 Key Considerations for CPS Security 147 7.4.1 Secure Design and Architecture Principles 148 7.4.1.1 Defense-in-Depth Strategy 148 7.4.1.2 Secure Communication Protocols 148 7.4.1.3 Access Control and Authentication Mechanisms 148 7.4.2 Threat Modeling and Risk Assessment 149 7.4.3 Intrusion Detection and Prevention Systems (IDPS) 149 7.4.4 Secure Software Development Practices 149 7.4.4.1 Secure Coding Guidelines 149 7.4.4.2 Code Reviews and Vulnerability Testing 150 7.5 Countermeasures for CPS Security 150 7.5.1 Network Security Measures 150 7.5.1.1 Firewalls and Network Segmentation 151 7.5.1.2 Idps 151 7.5.2 Physical Security Controls 151 7.5.2.1 Access Controls and Physical Barriers 151 7.5.2.2 Surveillance and Monitoring Systems 152 7.5.3 Incident Response and Recovery Plans 152 7.5.3.1 Incident Handling Procedures 152 7.5.3.2 Backup and Disaster Recovery Strategies 152 7.5.4 Security Awareness and Training Programs 153 7.6 Case Studies and Examples 153 7.6.1 Case Study 1: Industrial Control System (ICS) Security 153 7.6.1.1 Countermeasures 153 7.6.2 Case Study 2: Smart Cities and Infrastructure Protection 154 7.6.2.1 Countermeasures 154 7.6.3 Case Study 3: Autonomous Vehicles and Transportation Systems 154 7.6.3.1 Countermeasures 154 7.7 Future Directions and Emerging Technologies 155 7.7.1 Impact of Emerging Technologies on CPS Security 155 7.7.2 Challenges and Opportunities in Securing CPS in the Future 156 7.8 Conclusion 156 References 157 8 Unraveling the Ethical Conundrum: Privacy Challenges in the Realm of Digital Forensics 161 Tushar Krishnamani and Parmila Dhiman 8.1 Introduction 161 8.2 Fundamental Concepts in Digital Forensics 162 8.3 Privacy Concerns in AI Technology: Security Systems and Cyber Forensics 163 8.4 Maintaining Integrity of Evidence in Forensic Investigations 165 8.5 Ethical Obligations of Forensic Investigators 166 8.6 Conclusion 171 References 171 9 IoT and Smart Device Security: Emerging Threats and Countermeasures 173 Akhilesh Kumar Singh, Ajeet Kumar Sharma, Surabhi Kesarwani, Pradeep Kumar Singh, Pawan Kumar Verma and Seshathiri Dhanasekaran 9.1 Introduction 173 9.2 The Growth of IoT and Smart Devices 174 9.3 Emerging Threat Landscape 175 9.4 Device Vulnerabilities and Exploits 176 9.5 Data Privacy and Leakage 177 9.5.1 Data Privacy Concerns in IoT 178 9.5.2 Data Leakage Concerns in IoT 178 9.6 Network Attacks and Amplification 178 9.6.1 Network Attacks in IoT 181 9.6.2 Amplification Attacks in IoT 182 9.6.3 Preventive Measures and Mitigation 182 9.7 Physical Attacks on Smart Devices 183 9.8 Supply Chain Risks in IoT Ecosystem 184 9.9 Lack of Standardization in IoT Security 185 9.10 Countermeasures and Best Practices 187 9.11 Conclusion and Future Directions 188 9.11.1 Future Directions and Countermeasures 188 References 188 10 Advanced Security for IoT and Smart Devices: Addressing Modern Threats and Solutions 191 Himanshu Sharma, Prabhat Kumar and Kavita Sharma 10.1 Introduction 192 10.1.1 Overview of IoT and Smart Devices 192 10.1.2 Importance of Security in IoT and Smart Devices 192 10.1.3 Scope of the Chapter 192 10.2 IoT and Smart Device Landscape 193 10.2.1 Growth and Adoption of IoT and Smart Devices 193 10.2.2 Types and Examples of IoT and Smart Devices 194 10.2.3 Challenges in Securing IoT and Smart Devices 195 10.3 Emerging Threats in IoT and Smart Device Security 196 10.3.1 Malware and Ransomware Attacks 197 10.3.2 Device Exploitation and Hijacking 197 10.3.3 Data Breaches and Privacy Concerns 198 10.3.4 Distributed Denial of Service (DDoS) Attacks 198 10.3.5 Supply Chain Attacks 198 10.3.6 Insider Threats 198 10.3.7 Physical Security Risks 199 10.4 Vulnerabilities in IoT and Smart Devices 199 10.4.1 Insecure Communication Protocols 199 10.4.2 Weak Authentication and Authorization 200 10.4.3 Lack of Security Updates and Patch Management 200 10.4.4 Default or Hardcoded Credentials 200 10.4.5 Lack of Device Integrity Verification 200 10.4.6 Insufficient Encryption 201 10.4.7 Inadequate Access Controls 201 10.5 Countermeasures and Best Practices 201 10.5.1 Secure Device Design and Development 202 10.5.2 Robust Authentication and Access Controls 202 10.5.3 Encryption and Secure Communication Protocols 203 10.5.4 Regular Security Updates and Patch Management 203 10.5.5 Device Monitoring and Anomaly Detection 203 10.5.6 User Education and Awareness 203 10.5.7 Network Segmentation and Isolation 204 10.6 Security Standards and Regulations 204 10.6.1 Industry Standards for IoT and Smart Device Security 204 10.6.2 Regulatory Landscape for IoT and Smart Devices 205 10.6.3 Compliance and Certification Programs 205 10.7 Security Testing and Assessment 206 10.7.1 Penetration Testing and Vulnerability Assessments 206 10.7.2 Code and Firmware Analysis 206 10.7.3 Network Monitoring and Intrusion Detection 206 10.7.4 Security Audits and Compliance Assessments 207 10.8 Incident Response and Recovery 207 10.8.1 Incident Detection and Response Planning 207 10.8.2 Data Backup and Recovery Strategies 208 10.8.3 Incident Investigation and Forensics 208 10.8.4 Communication and Public Relations 208 10.9 Case Studies: Real-World Examples 209 10.9.1 Notable IoT and Smart Device Security Breaches 209 10.9.1.1 Mirai Botnet Attack 209 10.9.1.2 Stuxnet Attack 209 10.9.1.3 Jeep Cherokee Hack 209 10.9.1.4 Equifax Data Breach 210 10.9.2 Lessons Learned and Mitigation Strategies 210 10.9.2.1 Strong Authentication and Access Controls 210 10.9.2.2 Regular Security Updates and Patch Management 210 10.9.2.3 Network Segmentation and Isolation 210 10.9.2.4 Threat Intelligence and Monitoring 210 10.9.2.5 User Education and Awareness 211 10.9.2.6 Security by Design 211 10.9.2.7 Collaboration and Information Sharing 211 10.10 Future Trends and Challenges 211 10.10.1 AI and Machine Learning in IoT Security 211 10.10.2 Edge Computing and Security Implications 212 10.10.3 Blockchain and Distributed Ledger Technology 212 10.10.4 Quantum Computing and Its Impact on Security 212 10.11 Conclusion 213 References 215 11 Threats and Countermeasures for IoT and Smart Devices 217 Amrit Suman, Preetam Suman, Sasmita Padhy, Roshan Jahan and Naween Kumar 11.1 Introduction 217 11.2 IoT Architecture 219 11.2.1 Perception Layer 219 11.2.2 Network Layer 220 11.2.3 Application Layer 220 11.2.4 The Transport Layer 221 11.2.5 The Processing Layer 221 11.2.6 The Business Layer 221 11.3 Security in the Application Layer of IoT 221 11.3.1 Messaging Protocols 222 11.3.1.1 MQTT “Message Queuing Telemetry Transport Protocol” 222 11.3.1.2 Constrained-Application Protocol (CoAp) 223 11.3.1.3 AMQP “Advanced Message Queuing Protocol” 224 11.3.1.4 Data Distribution Service (DDS) 225 11.3.1.5 Extensible Messaging Protocol (XMPP) 225 11.3.2 Service Protocols 226 11.3.2.1 Multicast Domain Name System (mDNS) 226 11.3.2.2 Simple Service Discovery Protocol (SSDP) 227 11.4 Literature Survey 227 11.4.1 Countermeasures and IoT Threat-Mitigation Techniques 230 11.5 Results and Discussion 232 11.6 Conclusion and Future Work 234 References 235 12 Insider Threat Detection and Prevention: New Approaches and Tools 241 Rakhi S., Sampada H. K., Arun Balodi, Shobha P. C. and Roshan Kumar 12.1 Introduction 241 12.2 Insider Attack: A Big Picture 246 12.3 Tools and Technology for Insider Threat Detection 249 12.3.1 User and Entity Behavior Analytics (UEBA) Platforms 249 12.3.2 Data Loss Prevention (DLP) Solutions 250 12.3.3 Endpoint Detection and Response (EDR) Platforms 252 12.3.4 Security Information and Event Management (SIEM) Systems 253 12.3.5 User Activity Monitoring (UAM) Solutions 254 12.3.6 Insider Threat Intelligence Platforms 254 12.3.7 Privileged Access Management (PAM) Solutions 255 12.3.8 Machine Learning and AI-Based Tools 255 12.3.9 Insider Threat Mitigation in Cloud Environments 256 12.3.10 Psychological and Behavioral Aspects 257 12.4 Results and Discussions 258 12.5 Conclusion 261 References 261 13 A Holistic Framework for Insider Threat Detection and Analysis Upon Security and Privacy for Data Management Services 263 A. Sheik Abdullah, Hanish Shyam, Sriram B., Arif Ansari and Subramanian Selvakumar 13.1 Introduction 263 13.1.1 Need for a Holistic Framework for Data Management Services 264 13.1.2 Problem Statement 266 13.1.3 Challenges in Developing a Holistic Framework for DMS 267 13.1.4 Characteristics of Effective Framework for DMS 268 13.1.5 Assumptions 269 13.2 Defining Insider Threats 270 13.2.1 Types of Insider Threats Targeting DMS 271 13.2.2 Precursor and Indicators 273 13.2.3 Expression of Insider Attacks 274 13.2.4 Incentives for Insider Attack 275 13.3 Know Your Critical Assets in Data Management Services 276 13.3.1 Identifying Assets in DMS 276 13.3.2 Data Classification and Segmentation 278 13.3.3 Challenges to Asset Identification 281 13.4 Insider Risk Management 282 13.4.1 Modern Risk Pain Points 282 13.4.2 Plan for Insider Risk Management 282 13.4.3 Conducting Risk Assessment 283 13.4.4 Risk Levels with Acceptance Criteria 284 13.4.5 Prioritization of Risk 284 13.5 Diving Deeper Into Holistic Framework 287 13.5.1 Administration and its Scope 287 13.5.1.1 Approaches and Tools 288 13.5.2 Technical and its Scope 291 13.5.2.1 Approaches and Tools 291 13.5.3 Physical and Its Scope 296 13.5.3.1 Approaches and Tools 296 13.6 Conclusion 299 References 299 14 Revolutionizing SEO: Exploring the Synergy of Blockchain Technology and Search Ecosystems 303 Bharti Aggarwal, Dinesh Rai and Naresh Kumar 14.1 Introduction 303 14.2 Features of Blockchain 305 14.3 Literature Review 306 14.4 Integrating Blockchain into Search Ecosystems for Enhancing SEO 309 14.5 Integration of Blockchain in Search Ecosystems 310 14.6 Concept of Decentralized Search Platforms and Role in SEO Improvement 311 14.7 Use Cases and Projects Illustrating Blockchain Integration in Search Ecosystems 312 14.8 Future Trends and Implications 315 14.9 Potential Implications for the SEO Industry and Online Marketing Strategies 316 14.10 Conclusion 318 References 318 15 Emerging Trends and Future Directions of Blockchain Technology in Education 325 Urvashi Sugandh, Priyanka Gaba, Arvind Panwar and Jyoti Agarwal 15.1 Introduction 325 15.1.1 Background on the Current State of Blockchain Technology in Education 326 15.1.2 Importance of Exploring Emerging Trends and Future Directions 327 15.1.3 Purpose of the Chapter 328 15.2 Overview of Blockchain Technology in Education 328 15.2.1 Review of Blockchain Technology’s Basics 328 15.2.2 Blockchain’s Current Uses in Education 328 15.2.3 The Value of Staying Current With Emerging Trends 329 15.3 Emerging Trends in Blockchain and Education 330 15.3.1 Lifelong Learning and Blockchain-Based Digital Credentials 331 15.3.2 Competency-Based Education and Blockchain 332 15.3.3 Learning Analytics and Blockchain 333 15.3.4 Learning Platforms and Marketplaces Driven by Blockchain 334 15.4 Implications for the Future of Education 335 15.4.1 Advancements in Blockchain Technology and Their Potential Impact 335 15.4.2 Benefits and Challenges of Adopting Emerging Blockchain Trends 336 15.4.3 Opportunities for Educational Institutions and Stakeholders 338 15.5 Future Directions for Blockchain in Education 340 15.5.1 Research Directions and Areas for Further Exploration 340 15.5.2 Integration of Emerging Technologies With Blockchain in Education 342 15.5.3 Scalability, Interoperability, and Standardization Challenges to Address 344 15.6 Conclusion 345 15.6.1 Overview of Important Emerging Trends and Their Consequences 345 15.6.2 Analysis of Blockchain’s Future Potential in Education 345 15.6.3 Final Thoughts on the Value of Adopting Emerging Trends and Directions 346 References 346 16 Social Engineering Attacks: Detection and Prevention 349 Manpreet Kaur Aiden, Sonia Chhabra, Shweta Mayor Sabharwal and Alaa Ali Hameed 16.1 Introduction 349 16.2 Phases of Social Engineering 351 16.2.1 Preparation 351 16.2.2 Choose a Target 352 16.2.3 Build a Relation 352 16.2.4 Manipulate a Relation 352 16.3 Methods of Social Engineering 352 16.3.1 Human-Centric Social Engineering 353 16.3.1.1 Impersonation 353 16.3.1.2 Eavesdropping 354 16.3.1.3 Shoulder Surfing 354 16.3.1.4 Dumpster Diving 354 16.3.1.5 Reverse Social Engineering 354 16.3.1.6 Piggybacking 355 16.3.1.7 Tailgating 355 16.3.1.8 Diversion Theft 355 16.3.1.9 Honey Trap 356 16.3.1.10 Baiting 356 16.3.1.11 Quid Pro Quo 356 16.3.1.12 Elicitation 356 16.3.2 Computer-Centric Social Engineering 357 16.3.2.1 Pop-Up Windows 357 16.3.2.2 Hoax Letters 357 16.3.2.3 Chain Letters 357 16.3.2.4 Instant Chat Messenger 357 16.3.2.5 Spam Email 357 16.3.2.6 Scareware 358 16.3.2.7 Phishing 358 16.3.3 Mobile-Centric Social Engineering 361 16.3.3.1 Publish Malicious Apps 361 16.3.3.2 Repackage Legitimate Apps 361 16.3.3.3 Untrusted Security Applications 362 16.3.3.4 SMS Phishing 362 16.4 Insider Threat 362 16.4.1 Types of Insider Threat 362 16.4.1.1 Privileged Users 363 16.4.1.2 Disgruntled Workers 363 16.4.1.3 Accident-Prone Employees 363 16.4.1.4 Undertrained Staff 363 16.4.1.5 Third Parties 363 16.4.2 Reasons for Insider Attacks 363 16.4.2.1 Financial Motivation 363 16.4.2.2 Theft of Confidential Data 364 16.4.2.3 Revenge 364 16.4.2.4 Future Competition 364 16.4.2.5 Performing Competitors’ Bidding 364 16.4.2.6 Public Impact 364 16.4.3 Insider Threat Statistics 364 16.4.4 Insider Threats Types 364 16.4.4.1 Malicious Insider 365 16.4.4.2 Negligent Insider 365 16.4.4.3 Professional Insider 365 16.4.4.4 Compromised Insider 365 16.4.4.5 Accidental Insider 366 16.5 Impersonation on Social Media Platforms 366 16.5.1 Social Engineering for Social Media Platforms 366 16.5.1.1 By Creating a False Profile 366 16.5.1.2 By Unauthorized Access 367 16.5.2 Impersonation on Facebook 367 16.6 Identity Theft 367 16.6.1 Different Types of Identity Theft 367 16.6.1.1 Child Identity Theft 368 16.6.1.2 Hacker Identity Theft 368 16.6.1.3 Monetary Identity Theft 368 16.6.1.4 Driver’s License Identity Theft 368 16.6.1.5 Policy Identity Theft 368 16.6.1.6 Healthcare Identity Theft 368 16.6.1.7 Tax Identity Theft 369 16.6.1.8 Identity Replication and Disguise 369 16.6.1.9 Artificial Identity Theft 369 16.6.1.10 Social Identity Theft 369 16.6.2 Methods Employed by Attackers to Steal Identities 369 16.6.2.1 Loss of Personal Items 369 16.6.2.2 Internet Searches 369 16.6.2.3 Social Engineering 370 16.6.2.4 Dumpster Diving and Shoulder Surfing 370 16.6.2.5 Phishing 370 16.6.2.6 Skimming 370 16.6.2.7 Pretexting 370 16.6.2.8 Pharming 370 16.6.2.9 Hacking (Compromising a User’s System) 370 16.6.2.10 Keyloggers and Password Stealers (Malware) 371 16.6.2.11 Wardriving 371 16.6.2.12 Mail Theft and Rerouting 371 16.7 Social Engineering Detection and Prevention 371 16.7.1 Preventing Social Engineering 371 16.7.1.1 Password Policies 372 16.7.1.2 Physical Security Policies 372 16.7.1.3 Defense Strategy 373 16.7.2 How to Defend Against Phishing Attacks? 373 16.7.3 Detecting Insider Threats 373 16.7.3.1 Insider Risk Controls 374 16.7.3.2 Deterrence Controls 374 16.7.3.3 Data Loss Prevention (DLP) and Identity and Access Management (IAM) 374 16.7.3.4 Detection Controls 374 16.7.4 Insider Threat Countermeasures 375 16.7.4.1 Segregation and Rotation of Responsibilities 375 16.7.4.2 Least Privileges 375 16.7.4.3 Controlled Access 375 16.7.4.4 Logging and Auditing 375 16.7.4.5 Employee Monitoring 375 16.7.4.6 Legal Policies 375 16.7.4.7 Archive Critical Data 375 16.7.4.8 Employee Cybersecurity Training 375 16.7.4.9 Employee Background Verification 376 16.7.4.10 Periodic Risk Assessment 376 16.7.4.11 User Privilege Monitoring 376 16.7.4.12 Credentials Deactivation for Terminated Employees 376 16.7.4.13 Regular Risk Evaluation 376 16.7.4.14 Layered Defense 376 16.7.4.15 Physical Security 376 16.7.4.16 Surveillance 376 16.7.4.17 Zero-Trust Model 376 16.7.4.18 Behavioral Analytics 377 16.7.5 Identity Theft Prevention 377 16.7.5.1 Ensure Your Name is Not on Marketing Lists 377 16.7.5.2 Securely Store or Shred Private Information Documents 377 16.7.5.3 Safeguard Credit Card Statements 377 16.7.5.4 Avoid Providing Sensitive Information via Phone 377 16.7.5.5 Retrieve Mail Promptly 377 16.7.5.6 Be Cautious of Personal Information Requests 377 16.7.5.7 Monitor Online Banking Activities 377 16.7.5.8 Use Caution When Sharing Personal Information Online 377 16.7.5.9 Implement Two-Step Verification 377 16.7.6 Suspicious Email Detection 377 16.7.6.1 Generic Greetings from Banks, Businesses, or Social Networking Sites 378 16.7.6.2 Emails from People in Your Address Book 378 16.7.6.3 Urgent Tones or Veiled Threats, Grammar or Spelling Errors 378 16.7.6.4 Links to Fake Websites, Offers Too Good to be True 378 16.7.6.5 Official-Looking Logos and Details from Reliable Sources 378 16.7.7 Anti-Phishing Toolbar 378 16.7.7.1 Netcraft Source 378 16.7.7.2 Phish Tank Source 378 16.7.8 Social Engineering: Targets and Prevention 379 16.7.9 Social Engineering Tools 379 16.8 Conclusion and Future Directions 379 References 381 17 Social Engineering Attacks in Industrial Internet of Things and Smart Industry: Detection and Prevention 389 Muhammad Muzamil Aslam, Kassim Kalinaki, Ali Tufail, Abdul Ghani Haji Naim, Madiha Zahir Khan and Sajid Ali 17.1 Introduction 390 17.2 Phases of Social Engineering Attacks 391 17.2.1 Discovery and Investigation 391 17.2.2 Deception and Hook 391 17.2.3 Attack 392 17.2.4 Retreat 392 17.3 Social Engineering Attacks in IoT and IIoT 392 17.4 Techniques of Social Engineering Attacks 393 17.4.1 Phishing 393 17.4.2 Angler Phishing 394 17.4.3 Business Email Compromise (BEC) 394 17.4.4 Pharming 394 17.4.5 Spear Phishing 394 17.4.6 Tabnabbing 395 17.4.7 Whaling 395 17.4.8 Baiting 395 17.4.9 Scareware 396 17.4.10 Diversion Theft 396 17.4.11 SMS Phishing 396 17.4.12 Pretexting 397 17.4.13 Quid Pro Quo 397 17.4.14 Tailgating 398 17.4.15 Voice Phishing/Vishing 398 17.4.16 Watering Hole 398 17.4.17 Advance Fee Scam 398 17.5 Social Engineering Attack Vectors 399 17.5.1 Compromised Email 400 17.5.2 Weak Credentials 400 17.5.3 Malicious Insider 400 17.5.4 Careless Insider 401 17.5.5 A Mole 401 17.5.6 Misconfiguration 401 17.5.7 Phishing 402 17.5.8 Ransomware 402 17.6 Social Engineering Attack Detection and Prevention Techniques 403 17.6.1 Security Awareness Training 403 17.6.2 Endpoint and Antivirus Security Tools 403 17.6.3 Penetration Testing 404 17.6.4 Build a Positive Security Culture 404 17.6.5 Implement Advanced Security Measures in the Industry 404 17.7 Real-World Social Engineering Attacks in the Industry 404 17.7.1 Carbanak Fraud 404 17.7.2 Fax Notice Scam 405 17.7.3 Dropbox 405 17.7.4 Deepfake Attack on UK Energy Company 405 17.7.5 The Sacramento Phishing Attack Exposes Health Information 405 17.8 Challenges and Future Prospective in Social Engineering Attacks 406 17.9 Future Prospective and Recommendations 406 17.10 Conclusion 407 References 407 18 Cloud Security Essentials: A Detailed Exploration 413 Abhishek Singh Vardia, Aarti Chaudhary, Shikha Agarwal, Anil Kumar Sagar and Gulshan Shrivastava 18.1 Introduction 413 18.2 The Importance of Cloud Security 414 18.2.1 Data Protection 414 18.2.2 Business Continuity 415 18.2.3 Compliance and Regulation 415 18.3 Key Cloud Security Concerns 415 18.3.1 Data Exploits 416 18.3.2 Insecure APIs 417 18.3.3 Compliance and Legal Issues 417 18.3.4 Insider Threats 418 18.3.5 Shared Responsibility Model 418 18.3.6 Vendor Lock-In 419 18.3.7 Lack of Transparency 419 18.3.8 Emerging Threats and Evolving Security 419 18.3.9 Network Security 419 18.3.10 Identity and Access Management (IAM) 420 18.3.11 Cloud-Shared Technology Risks 420 18.3.12 Cloud Compliance and Auditing 420 18.3.13 Data Encryption 421 18.3.14 Cloud-Based Applications 421 18.3.15 DevOps and Continuous Integration/Continuous Deployment (ci/cd) 421 18.4 Cloud Security Challenges 422 18.4.1 Data Security and Privacy Concerns 422 18.4.2 Identity and Access Management (IAM) 423 18.4.3 Network Security Challenges 424 18.4.4 Evolving Threat Landscape 424 18.4.5 Vendor Lock-In 425 18.4.6 Lack of Cloud Security Expertise 425 18.5 Cloud Security Challenges and Strategies 425 18.6 Common Threats in Cloud Security 426 18.6.1 Unauthorized Access 426 18.6.2 Data Breaches 426 18.6.3 DDoS Attacks 427 18.7 Best Practices for Cloud Security 427 18.7.1 Data Security 428 18.7.2 Identity and Access Management (IAM) 429 18.7.3 Network Security 429 18.7.4 Adaptation to Threats 429 18.7.5 Vendor Lock-In Mitigation 430 18.7.6 Human Element in Security 430 18.8 Conclusion 430 References 431 19 Data Privacy and Protection: Legal and Ethical Challenges 433 Oladri Renuka, Niranchana RadhaKrishnan, Bodapatla Sindhu Priya, Avula Jhansy and Soundarajan Ezekiel 19.1 Introduction 433 19.2 Fundamental Concepts of Data Privacy and Protection 435 19.2.1 Data Privacy and Protection 435 19.2.2 Importance of Personal Data in the Digital Age 435 19.2.3 Relationship Between Privacy and Data Protection 436 19.2.3.1 Privacy as an Individual Right 436 19.2.3.2 Data Protection as Organizational Responsibility 436 19.2.3.3 The Symbiotic Balance 436 19.2.3.4 Navigating the Digital Landscape 437 19.3 Legal Frameworks for Data Privacy and Protection: Overview of Global Data Protection Laws 437 19.3.1 Comparative Analysis of Jurisdictional Approaches 439 19.4 Rights and Principles Underpinning Data Privacy 440 19.4.1 Right to Privacy as a Human Right 440 19.4.2 Consent and Its Function in Data Processing 441 19.4.3 Data Minimization, Purpose Limitation, and Accountability 442 19.5 Challenges in Implementing Data Privacy Regulations 442 19.5.1 Challenges for Businesses and Organizations 442 19.5.2 Balancing Operational Efficiency and Compliance 445 19.5.3 Navigating Cross-Border Data Transfers 445 19.6 Ethical Considerations in Data Collection and Usage: Transparency and Informed Consent 446 19.6.1 Transparency: Fostering Trust Through Openness 447 19.6.2 Minimizing Algorithmic Bias: Preserving Fairness and Equality 448 19.6.3 Ethical Responsibilities of Data Controllers and Processors 448 19.7 Emerging Technologies and Ethical Dilemmas: Impact of AI, IoT, and Biometrics on Data Privacy 449 19.7.1 Impact of AI, IoT, and Biometrics on Data Privacy 449 19.7.1.1 Impact of AI on Data Privacy: Balancing Innovation and Privacy 449 19.7.1.2 Impact of IoT on Data Privacy: Security and Consent Challenges 449 19.7.1.3 Biometrics’ Effect on Data Privacy: Juggling Privacy and Convenience 450 19.7.2 Ethical Challenges in Data Analytics and Profiling: Balancing Insight and Privacy 450 19.7.2.1 Privacy-Preserving Techniques and Solutions: Balancing Utility and Confidentiality 451 19.8 Legal and Ethical Reactions to Data Breach and Privacy Incidents: Legal Requirements for Notifying Data Breach 452 19.8.1 Legal Obligations in Data Breach Notification: Ensuring Transparency and Accountability 452 19.8.1.1 Balancing Legal Obligations with Ethical Considerations 452 19.8.2 Ethical Handling of Data Breach Fallout: Mitigating Harm and Restoring Trust 453 19.8.3 Case Studies: Lessons From High-Profile Data Breaches 453 19.9 Surveillance, National Security, and Individual Privacy: Striking a Balance: Privacy vs. National Security 454 19.9.1 Striking a Balance: Privacy vs. National Security 454 19.9.2 Ethics of Mass Surveillance and Data Retention: Balancing Security and Privacy 455 19.9.3 Maintaining Civil Rights in the Digital Age: Finding the Moral Middle Ground 456 19.10 Regulatory Enforcement and Accountability: Role of Data Protection Authorities 456 19.10.1 Role of Data Protection Authorities: Guardians of Data Privacy 457 19.10.1.1 Impact of Data Protection Authorities 457 19.10.2 Penalties, Fines, and Recourse for Non-Compliance: Dissuading Infractions 458 19.10.3 Corporate Social Responsibility in Data Protection: Ethical and Social Commitments 458 19.11 Future Trends and Considerations: Evolving Legal Landscapes and Global Harmonization 459 19.11.1 Evolving Legal Landscapes: Adapting to Technological Change 460 19.11.1.1 Global Harmonization: Navigating Cross-Border Data Flow 460 19.11.2 Ethical Standards for Innovation Driven by Data: Handling the Complexity of Ethics 461 19.11.3 The Role of Education and Public Awareness: Empowering Informed Choices 461 19.12 Conclusion: Navigating the Nexus of Data Privacy and Protection 462 19.12.1 Synthesis of Legal and Ethical Challenges Explored 462 19.12.2 Call for Collaborative Efforts in Data Privacy and Protection 463 19.12.3 Ensuring a Balanced and Responsible Data Ecosystem 463 Conclusion 463 References 463 20 Future Direction in Digital Forensics and Cyber Security 467 Ar. Varsha, Nayana Anoop Kumar, Sosthenes Nyabuto Bichanga and Pooja Chakraborty 20.1 Introduction 467 20.2 Evolution of Crime 468 20.3 Existing Cybercrime Rate in India and World 468 20.3.1 Cybercrimes in India 469 20.3.1.1 Case Studies—Cybercrime in India 470 20.3.2 Cybercrime Worldwide—An Overview 471 20.3.2.1 Case Studies—Cybercrime Worldwide 472 20.4 Emerging Cybercrime and its Future 472 20.4.1 Internet of Things (IoT) Attacks 472 20.4.1.1 Case Study: Mirai Botnet 473 20.4.1.2 Prevention from the Internet of Things Attacks 473 20.4.1.3 Future of the Internet of Things Attacks 473 20.4.2 Audio Cloning 473 20.4.2.1 Consequences of Audio Cloning Artificial Intelligence 474 20.4.2.2 Future of AI Voice Cloning 474 20.4.3 Cryptocurrency Scams 474 20.4.3.1 Case Study: Ronin Network Crypto Heist 475 20.4.3.2 Prevention from Cryptocurrency Scams/Crypto Jacking 475 20.4.4 Cyberterrorism 475 20.4.4.1 Reasons for the Predominance of Cyberterrorism 475 20.4.5 Social Media Forensics 476 20.4.5.1 What is Social Media? 476 20.4.5.2 Understanding Social Media 477 20.4.5.3 Major Platforms of Social Media 477 20.4.5.4 What does Social Media Contain? 477 20.4.5.5 Nature of Social Media Crime 478 20.4.5.6 Examples of Social Media Crimes 478 20.4.5.7 Use of Social Media in Forensic Investigation 478 20.4.5.8 Tools for Detecting and Investigating Crime on Social Media 479 20.4.5.9 How can Fraud be Detected Using Social Media 480 20.5 Recent Paradigm Shift in Cyber Menace 480 20.5.1 Online Game: A New Approach to Cybercrime 481 20.5.1.1 Crimes Committed Through Online Gaming 481 20.5.1.2 Prevention from Online Gaming Crimes 482 20.5.2 Dark Web 482 20.5.2.1 Future of the Dark Web 483 20.5.2.2 Prevention from the Dark Web 483 20.6 Cyber Security 484 20.6.1 Future of Cyber Security 484 20.6.2 Threats of Future Cyber Security 485 20.7 Artificial Intelligence 485 20.7.1 Limitations of Artificial Intelligence 486 20.7.2 Threats of Artificial Intelligence in the Future 487 20.7.2.1 Deep Fake Attack 487 20.7.2.2 AI Phishing Attack 487 20.7.2.3 DoS Attack 487 20.7.2.4 Advanced Persistent Threat 488 20.7.2.5 Data Processing Giant 488 20.8 Contemporary Condition of Digital Forensics 488 20.9 Challenges of Digital Forensics 489 20.10 Legal Aspect of Cyber Laws 489 20.11 Prevention Against Cybercrimes 491 20.12 Conclusion 492 References 492 Index 495