This project aims to design an insider threat detection system that analyzes user behavior and system logs to detect suspicious internal activities. It supports forensic investigations by identifying abnormal access patterns and potential data misuse.
Study insider threat models and real-world case studies.
Collect and analyze system login and file access logs.
Design user behavior profiling techniques based on access frequency and timing.
Implement anomaly detection logic to identify deviations from normal behavior.
Create risk scoring mechanisms for suspicious activities.
Generate visual dashboards displaying behavioral patterns.
Develop alert notifications for high-risk user activities.
Test the system using simulated insider misuse scenarios.
Validate detection accuracy and minimize false positives.
Document findings and recommendations for organizational security.
