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International Journal of Computer Techniques Volume 12 Issue 4 | Smarter Cyber Defence: Using Hierarchical Explainable AI to Detect APT29

Smarter Cyber Defence: Using Hierarchical Explainable AI to Detect APT29

Smarter Cyber Defence: Using Hierarchical Explainable AI to Detect APT29

International Journal of Computer Techniques – Volume 12 Issue 4, July – August 2025

ISSN: 2394-2231 | https://ijctjournal.org

Authors

Anugra P Jose – VTU26905, Vel Tech University | vtu26905@veltech.edu.in

Dr. Priya P. Sajan – Senior Project Engineer, C-DAC Thiruvananthapuram | priyasajan@cdac.in

Abstract

This case study investigates the SolarWinds cyberattack and the role of AI in detecting Advanced Persistent Threats (APTs) like APT29 (CozyBear). It introduces LiteAI-MD, an AI-powered malware detection system that uses hierarchical explainability and pre-execution scanning to identify threats. The study highlights how AI enhances digital forensics, anomaly detection, and supply chain security, offering a proactive defense against stealthy cyber-espionage campaigns.

Keywords

APT29, CozyBear, LiteAI-MD, Explainable AI, Malware Detection, Supply Chain Attack, Cybersecurity, SolarWinds Hack

Conclusion

Traditional malware detection systems are inadequate against stealthy APTs like APT29. LiteAI-MD addresses this gap by scanning software updates before execution, using AI-driven classification and threat intelligence. Its hierarchical explainability improves transparency and trust. This proactive approach strengthens supply chain security and demonstrates the critical role of AI in modern cyber defense strategies.

References

  1. Wikipedia. “Cozy Bear.” 2024. https://en.wikipedia.org/wiki/CozyBear
  2. M. Cobb. “SolarWinds Hack Explained.” TechTarget, 2023.
  3. S. Rashid. “Limitations of Signature-Based Malware Detection.” IEEE Transactions on Cybersecurity, 2019.
  4. H. Singh et al. “Evasion Techniques Used by Modern Malware.” IJNS, 2021.
  5. ReversingLabs. “Software Supply Chain Security Solutions.” 2023.
  6. T. Balarabe. “The SolarWinds Hack.” Medium, 2024.
  7. Snyk. “Software Composition Analysis Tools.” 2022.
  8. JFrog. “Xray: Security Scanning for Software Artifacts.” 2023.
  9. T. Ahmad. “AI for Cybersecurity: A Review.” JIS, 2021.
  10. R. Khandelwal & M. Gupta. “AI-based Malware Detection.” IEEE Access, 2022.
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