International Journal on Science and Technology

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Insider Threat Monitoring Frameworks: Leveraging Behavioral Analytics

Author(s) Sabeeruddin Shaik
Country United States
Abstract Insider threats provide a significant risk to organizational security due to their access to essential systems and sensitive information. This article examines how behavioral analytics might improve insider threat monitoring systems, providing firms with preemptive methods to identify and mitigate potential risks. Utilizing machine learning and artificial intelligence (AI), behavioral analytics facilitates real-time monitoring and anomaly detection, hence enhancing organizational resilience. This study explores the issue statement, proposes a solution through behavioral analytics, and assesses its applications, effects, and extent. This study also addresses the problems and future prospects of behavioral analytics for insider threat detection, enabling firms to adapt to changing security environments. Emphasis is placed on incorporating behavioral models, ethical considerations, and organizational preparedness for implementing these solutions.
Keywords Insider Threats, Behavioral Analytics, Cybersecurity, Anomaly Detection, Machine Learning, Monitoring Frameworks, Proactive Security, Insider Threat Management, Data Security.
Field Engineering
Published In Volume 15, Issue 2, April-June 2024
Published On 2024-05-08
Cite This Insider Threat Monitoring Frameworks: Leveraging Behavioral Analytics - Sabeeruddin Shaik - IJSAT Volume 15, Issue 2, April-June 2024. DOI 10.5281/zenodo.14752331
DOI https://doi.org/10.5281/zenodo.14752331
Short DOI https://doi.org/g826tm
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