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Chapter 1 Emerging Cyber Threats: Challenges, Impacts, and Proactive Defenses in the Digital Age

  • Vignesh Krishna Vajha , Bryan Bovas Mathew and Ruchi Jakhmola Mani
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Cybersecurity Unlocked
This chapter is in the book Cybersecurity Unlocked

Abstract

People, organizations, and governments are facing major challenges due to the unprecedented increase in cyber threats and attacks caused by the rapid advances in technology and digital connectivity. Malware, ransomware, phishing, distributed denial-of-service attacks, and advanced persistent threats) are among the top cyber threats categorized, and their mechanisms of action and potential impact are explained. Attention is also paid to advanced threats such as supply chain attacks, zero-day exploits, and the Increasing dangers of modern technologies such as cloud computing, artificial intelligence (AI), and the Internet of Things. The chapter documents the evolution of cyber threats, with a focus on the shift from viruses to advanced ransomware as a service and AI-based attacks. The difficulties in identifying and preventing new threats such as encrypted traffic and polymorphic malware are also addressed. The importance of using indicators of compromise to identify possible attacks and the need for strong threat intelligence is emphasized. It also examines the reasons behind cybercrime, ranging from espionage and hacktivism to political agendas and financial gain. It draws attention to the weaknesses that adversaries exploit and the far-reaching impact these attacks have on national security, the economy, and privacy. Finally, it emphasizes the need for proactive defensive tactics instead of reactive such as in-depth threat intelligence, incident response planning, and comprehensive cybersecurity policies to address these escalating threats. It also discusses the importance of helping people and organizations develop a cybersecurity culture to successfully reduce risk through a detailed explanation.

Abstract

People, organizations, and governments are facing major challenges due to the unprecedented increase in cyber threats and attacks caused by the rapid advances in technology and digital connectivity. Malware, ransomware, phishing, distributed denial-of-service attacks, and advanced persistent threats) are among the top cyber threats categorized, and their mechanisms of action and potential impact are explained. Attention is also paid to advanced threats such as supply chain attacks, zero-day exploits, and the Increasing dangers of modern technologies such as cloud computing, artificial intelligence (AI), and the Internet of Things. The chapter documents the evolution of cyber threats, with a focus on the shift from viruses to advanced ransomware as a service and AI-based attacks. The difficulties in identifying and preventing new threats such as encrypted traffic and polymorphic malware are also addressed. The importance of using indicators of compromise to identify possible attacks and the need for strong threat intelligence is emphasized. It also examines the reasons behind cybercrime, ranging from espionage and hacktivism to political agendas and financial gain. It draws attention to the weaknesses that adversaries exploit and the far-reaching impact these attacks have on national security, the economy, and privacy. Finally, it emphasizes the need for proactive defensive tactics instead of reactive such as in-depth threat intelligence, incident response planning, and comprehensive cybersecurity policies to address these escalating threats. It also discusses the importance of helping people and organizations develop a cybersecurity culture to successfully reduce risk through a detailed explanation.

Chapters in this book

  1. Frontmatter I
  2. Contents V
  3. Chapter 1 Emerging Cyber Threats: Challenges, Impacts, and Proactive Defenses in the Digital Age 1
  4. Chapter 2 Silent Guardians: Proactive Approaches to Modern Cyber Threats 31
  5. Chapter 3 Data Science for Threat Detection and Analysis 59
  6. Chapter 4 An Integrated Approach: Merging Cybersecurity, AI, and Threat Detection 87
  7. Chapter 5 Cybersecurity Analytics: A Review of Challenges and the Role of Machine Learning and Deep Learning in Threat Detection 103
  8. Chapter 6 Hardware-Based Authentication Techniques for Secure Data Transmission in IoT Edge Computing 141
  9. Chapter 7 Securing the IoT Networks Using a Deep Learning Paradigm for Intrusion Detection 161
  10. Chapter 8 Hybrid Malware Detection and Classification Using Explainable Deep Neural Network 177
  11. Chapter 9 Light POW for Smart Grid Communication 201
  12. Chapter 10 Zero Trust Architecture – A Beginner’s Guide 227
  13. Chapter 11 Post-quantum Cryptography for Enhanced Authentication in Mobile Data Communication: Resilience Against Quantum Attacks 265
  14. Chapter 12 Two-Factor Authentication (2FA) and Multi-factor Authentication (MFA) Solutions for Secure Mobile Data Communication 287
  15. Chapter 13 Artificial Intelligence and Machine Learning in Cybersecurity 313
  16. Chapter 14 Enhancing IoT Security with Zero Trust Networking: Protecting Wireless Sensors, Edge Devices, and Cloud Environments 343
  17. Chapter 15 Biometric Authentication Methods for Mobile Devices: Exploring Fingerprint, Face Recognition, and Iris Scanning 365
  18. Chapter 16 Robust Dynamic Voice-Based Key Generation Using Novel Fuzzy Extraction, Averaged Thresholding, and Hamming Enhancement Techniques 385
  19. Chapter 17 Enhancing Cybersecurity with Artificial Intelligence and Machine Learning Techniques 413
  20. Chapter 18 Firewall and IDS in Cybersecurity 439
  21. Index
https://doi.org/10.1515/9783111712895-001

Chapters in this book

  1. Frontmatter I
  2. Contents V
  3. Chapter 1 Emerging Cyber Threats: Challenges, Impacts, and Proactive Defenses in the Digital Age 1
  4. Chapter 2 Silent Guardians: Proactive Approaches to Modern Cyber Threats 31
  5. Chapter 3 Data Science for Threat Detection and Analysis 59
  6. Chapter 4 An Integrated Approach: Merging Cybersecurity, AI, and Threat Detection 87
  7. Chapter 5 Cybersecurity Analytics: A Review of Challenges and the Role of Machine Learning and Deep Learning in Threat Detection 103
  8. Chapter 6 Hardware-Based Authentication Techniques for Secure Data Transmission in IoT Edge Computing 141
  9. Chapter 7 Securing the IoT Networks Using a Deep Learning Paradigm for Intrusion Detection 161
  10. Chapter 8 Hybrid Malware Detection and Classification Using Explainable Deep Neural Network 177
  11. Chapter 9 Light POW for Smart Grid Communication 201
  12. Chapter 10 Zero Trust Architecture – A Beginner’s Guide 227
  13. Chapter 11 Post-quantum Cryptography for Enhanced Authentication in Mobile Data Communication: Resilience Against Quantum Attacks 265
  14. Chapter 12 Two-Factor Authentication (2FA) and Multi-factor Authentication (MFA) Solutions for Secure Mobile Data Communication 287
  15. Chapter 13 Artificial Intelligence and Machine Learning in Cybersecurity 313
  16. Chapter 14 Enhancing IoT Security with Zero Trust Networking: Protecting Wireless Sensors, Edge Devices, and Cloud Environments 343
  17. Chapter 15 Biometric Authentication Methods for Mobile Devices: Exploring Fingerprint, Face Recognition, and Iris Scanning 365
  18. Chapter 16 Robust Dynamic Voice-Based Key Generation Using Novel Fuzzy Extraction, Averaged Thresholding, and Hamming Enhancement Techniques 385
  19. Chapter 17 Enhancing Cybersecurity with Artificial Intelligence and Machine Learning Techniques 413
  20. Chapter 18 Firewall and IDS in Cybersecurity 439
  21. Index
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