Advanced Threat Detection with Active Directory and SIEM
Advanced Threat Detection with Active Directory and SIEM
Dr. Swapna S
2025 · DOI: 10.22214/ijraset.2025.68478
International Journal for Research in Applied Science and Engineering Technology · 0 Citations
TLDR
A scalable, intelligence-driven security model that combines automation, system administration, and cybersecurity best practices to safeguard enterprise environments is demonstrated, which leverages machine learning-based detection for proactive cyber defense.
Abstract
As cyber threats become more sophisticated, traditional security mechanisms relying solely on Active Directory (AD)
for authentication and authorization lack real-time threat detection and response capabilities. This project enhances security byintegrating AD with Splunk, a Security Information and Event Management (SIEM) solution, within a virtualized environmentwhere Microsoft Server 2022 hosts AD services and a Domain Controller, while Splunk provides centralized security monitoring.PowerShell scripting automates user management and event log monitoring, improving administrative efficiency. To evaluatesystem effectiveness, a simulated password-cracking attack from a Linux machine (IP: 192.168.10.250) targets the AD server,with Splunk monitoring security logs for real-time anomaly detection, automated threat alerts, and advanced analytics to identifyunauthorized access attempts, privilege escalation, and insider threats. The network setup includes grydsecurity, featuring anActive Directory Server (192.168.10.7), a Splunk Server (192.168.10.10), and a DHCP-connected client PC, with RDP restrictedon client machines to prevent remote attacks but accessible on the server for administrative purposes. By integrating AD withSplunk SIEM, this system strengthens IT infrastructure security, enhances incident response, ensures compliance withregulatory frameworks such as HIPAA and GDPR, and leverages machine learning-based detection for proactive cyber defense.This project demonstrates a scalable, intelligence-driven security model that combines automation, system administration, andcybersecurity best practices to safeguard enterprise environments.