AI in Data Exfiltration Forensics: Tracking Stolen Information
-
Abnormal Data Movement Detection
AI identifies unusual file transfers, upload spikes, and outbound traffic patterns linked to data theft. -
Content Fingerprinting
Machine learning creates data fingerprints to trace stolen files even after renaming or compression. -
Cross-System Correlation
AI links endpoint activity, network logs, and cloud access records to reconstruct exfiltration paths. -
Insider vs External Attribution
AI analyzes access behavior to distinguish insider-driven leaks from external attacks. -
Visual Evidence Mapping
AI generates clear flow maps showing how data moved and where it exited.
πΉ Bottom Line: AI transforms data exfiltration forensics by making hidden data theft visible and traceable.

Comments
Post a Comment