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.
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.
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