Advanced Threat Detection with Active Directory and SIEM

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 by integrating AD with Splunk, a Security Information and Event Management (SIEM) solution, within a virtualized environment where 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 evaluate system 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 identify unauthorized access attempts, privilege escalation, and insider threats. The network setup includes grydsecurity, featuring an Active Directory Server (192.168.10.7), a Splunk Server (192.168.10.10), and a DHCP-connected client PC, with RDP restricted on client machines to prevent remote attacks but accessible on the server for administrative purposes. By integrating AD with Splunk SIEM, this system strengthens IT infrastructure security, enhances incident response, ensures compliance with regulatory 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, and cybersecurity best practices to safeguard enterprise environments.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-04-17
DOI
https://doi.org/10.22214/ijraset.2025.68478
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
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article

Advanced Threat Detection with Active Directory and SIEM

Swapna S
International Journal for Research in Applied Science and Engineering Technology
Advanced Malware Detection Techniques
article

Advanced Threat Detection with Active Directory and SIEM

Swapna S
article en

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 by integrating AD with Splunk, a Security Information and Event Management (SIEM) solution, within a virtualized environment where 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 evaluate system 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 identify unauthorized access attempts, privilege escalation, and insider threats. The network setup includes grydsecurity, featuring an Active Directory Server (192.168.10.7), a Splunk Server (192.168.10.10), and a DHCP-connected client PC, with RDP restricted on client machines to prevent remote attacks but accessible on the server for administrative purposes. By integrating AD with Splunk SIEM, this system strengthens IT infrastructure security, enhances incident response, ensures compliance with regulatory 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, and cybersecurity best practices to safeguard enterprise environments.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(4)
Openalex Percentile: Top 91%
Advanced Malware Detection Techniques
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