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Articles

Vol. 2 No. 1 (2022): Cybersecurity and Network Defense Research (CNDR)

Cyber Threat Hunting: Exploring Methods and Tools for Proactive Cyber Threat Hunting to Identify and Neutralize Advanced Persistent Threats (APTs) and Insider Threats

Published
25-07-2024

Abstract

Cyber Threat Hunting (CTH) has emerged as a critical practice for organizations to proactively identify and mitigate cyber threats. This paper presents an in-depth analysis of the methods and tools used in CTH, focusing on the detection and neutralization of Advanced Persistent Threats (APTs) and insider threats. The paper begins by defining CTH and its importance in modern cybersecurity. It then explores various methods used in CTH, including signature-based detection, anomaly detection, and behavioral analysis. The paper also discusses the role of threat intelligence and machine learning in enhancing CTH capabilities.

Additionally, the paper examines the tools and technologies commonly used in CTH, such as Security Information and Event Management (SIEM) systems, Endpoint Detection and Response (EDR) solutions, and Threat Intelligence Platforms (TIPs). The paper provides a comparative analysis of these tools, highlighting their strengths and limitations in the context of CTH.

Overall, this paper aims to provide cybersecurity professionals and researchers with a comprehensive understanding of the methods and tools available for proactive cyber threat hunting, enabling them to better defend against APTs and insider threats.

References

  1. References
  2. Pargaonkar, Shravan. "A Review of Software Quality Models: A Comprehensive Analysis." Journal of Science & Technology 1.1 (2020): 40-53.
  3. Raparthi, Mohan, Sarath Babu Dodda, and SriHari Maruthi. "Examining the use of Artificial Intelligence to Enhance Security Measures in Computer Hardware, including the Detection of Hardware-based Vulnerabilities and Attacks." European Economic Letters (EEL) 10.1 (2020).
  4. Pargaonkar, Shravan. "Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering." Journal of Science & Technology 1.1 (2020): 61-66.
  5. Raparthi, Mohan, Sarath Babu Dodda, and Srihari Maruthi. "AI-Enhanced Imaging Analytics for Precision Diagnostics in Cardiovascular Health." European Economic Letters (EEL) 11.1 (2021).
  6. Pargaonkar, Shravan. "Future Directions and Concluding Remarks Navigating the Horizon of Software Quality Engineering." Journal of Science & Technology 1.1 (2020): 67-81.
  7. Vyas, Bhuman. "Ensuring Data Quality and Consistency in AI Systems through Kafka-Based Data Governance." Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal 10.1 (2021): 59-62.
  8. Pargaonkar, Shravan. "Quality and Metrics in Software Quality Engineering." Journal of Science & Technology 2.1 (2021): 62-69.
  9. Pargaonkar, Shravan. "The Crucial Role of Inspection in Software Quality Assurance." Journal of Science & Technology 2.1 (2021): 70-77.
  10. Vyas, Bhuman. "Optimizing Data Ingestion and Streaming for AI Workloads: A Kafka-Centric Approach." International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068 1.1 (2022): 66-70.
  11. Rajendran, Rajashree Manjulalayam. "Scalability and Distributed Computing in NET for Large-Scale AI Workloads." Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal 10.2 (2021): 136-141.
  12. Pargaonkar, Shravan. "Unveiling the Future: Cybernetic Dynamics in Quality Assurance and Testing for Software Development." Journal of Science & Technology 2.1 (2021): 78-84.
  13. Vyas, Bhuman. "Ethical Implications of Generative AI in Art and the Media." International Journal for Multidisciplinary Research (IJFMR), E-ISSN: 2582-2160.
  14. Rajendran, Rajashree Manjulalayam. "Exploring the Impact of ML NET (http://ml. net/) on Healthcare Predictive Analytics and Patient Care." Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal 11.1 (2022): 292-297.
  15. Pargaonkar, Shravan. "Unveiling the Challenges, A Comprehensive Review of Common Hurdles in Maintaining Software Quality." Journal of Science & Technology 2.1 (2021): 85-94.
  16. Pargaonkar, S. (2020). A Review of Software Quality Models: A Comprehensive Analysis. Journal of Science & Technology, 1(1), 40-53.
  17. Raparthi, M., Dodda, S. B., & Maruthi, S. (2020). Examining the use of Artificial Intelligence to Enhance Security Measures in Computer Hardware, including the Detection of Hardware-based Vulnerabilities and Attacks. European Economic Letters (EEL), 10(1).
  18. Pargaonkar, S. (2020). Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering. Journal of Science & Technology, 1(1), 61-66.
  19. Raparthi, M., Dodda, S. B., & Maruthi, S. (2021). AI-Enhanced Imaging Analytics for Precision Diagnostics in Cardiovascular Health. European Economic Letters (EEL), 11(1).
  20. Vyas, B. (2021). Ensuring Data Quality and Consistency in AI Systems through Kafka-Based Data Governance. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 10(1), 59-62.
  21. Rajendran, R. M. (2021). Scalability and Distributed Computing in NET for Large-Scale AI Workloads. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 10(2), 136-141.
  22. Pargaonkar, S. (2020). Future Directions and Concluding Remarks Navigating the Horizon of Software Quality Engineering. Journal of Science & Technology, 1(1), 67-81.
  23. Vyas, B. (2022). Optimizing Data Ingestion and Streaming for AI Workloads: A Kafka-Centric Approach. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 1(1), 66-70.
  24. Pargaonkar, S. (2021). Quality and Metrics in Software Quality Engineering. Journal of Science & Technology, 2(1), 62-69.
  25. Vyas, B. Ethical Implications of Generative AI in Art and the Media. International Journal for Multidisciplinary Research (IJFMR), E-ISSN, 2582-2160.
  26. Rajendran, R. M. (2022). Exploring the Impact of ML NET (http://ml. net/) on Healthcare Predictive Analytics and Patient Care. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 11(1), 292-297.
  27. Pargaonkar, S. (2021). The Crucial Role of Inspection in Software Quality Assurance. Journal of Science & Technology, 2(1), 70-77.
  28. Pargaonkar, S. (2021). Unveiling the Future: Cybernetic Dynamics in Quality Assurance and Testing for Software Development. Journal of Science & Technology, 2(1), 78-84.
  29. Pargaonkar, S. (2021). Unveiling the Challenges, A Comprehensive Review of Common Hurdles in Maintaining Software Quality. Journal of Science & Technology, 2(1), 85-94.