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AI-Driven Insider Threat Detection Using Wazuh and Behavioral Analytics: A Modular Approach

Year: 2025

Type: article

Abstract: : Insider threats represent a critical challengein modern cybersecurity, ofteneluding traditional defensesduet othe irsubtletyandlegit- imateaccess. ThispaperpresentsanAI-drivende- tectionsystemintegratingtheopen-sourceWazuh SIEM platform with behavioral analytics and machine learning. Leveraging the CERT Insider Threat Dataset and real-time log ingestion, the system employs supervised learning models to identifyanomalousbehavior,assigndynamicrisk scores, and provide actionable alerts. The modular architecture ensures scalability and effective threatvisualization, demonstratingproactive de- tection capabilities with reduced false positives through continuous learning.

Source: International Journal for Research in Applied Science and Engineering Technology

DOI: 10.22214/ijraset.2025.70284

Author: Navaneet R Rao

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4410156729

FWCI:

Cites: 3

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Related to: 10