• M Akshay
• Shivaraju N
• Puneeth M

Insider threats pose a significant security risk as they originate from trusted users within-an organization. In this project, we would like to propose Insider Threat Detection-system through User Behavior Analytic (UBA) which identifies activities of users outside of their normal behavior. The system will analyze user behavior, establish a baseline of normal behavior of the user, and use machine learning methods to detect abnormal behavior. Suspicious behaviors such as login from another location or access to data by the user can trigger alerts to help mitigate a data breach caused by an insider. UBA provides enhanced security for organizations by reducing the response time to identify and investigate use cases of insider threats.

Insider Threat, User Behavior Analytics, Machine Learning, Anomaly Detection, Risk Scoring, Behavioral Baseline, Real-time Monitoring, Rule-Based Engine, Data Exfiltration, Django, React.js, PostgreSQL, Isolation Forest, Alert Correlation, UEBA

" Insider Threat Detection Using User Behaviour Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 12, page no.a112-a120, December-2025, Available :http://www.jetir.org/papers/JETIR2512015.pdf

" Insider Threat Detection Using User Behaviour Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 12, page no. ppa112-a120, December-2025, Available at : http://www.jetir.org/papers/JETIR2512015.pdf