Insider Threat Detection Model Using Anomaly-Based Isolation Forest Algorithm

Insider Threat Detection Model Using Anomaly-Based Isolation Forest Algorithm

Insider attacks may inflict far greater damage to an organization than outsider threats since insiders are authorized users who are acquainted with the business’s system, making detection harder. Many techniques to detecting insider threats have been developed, but they are neither flexib...

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Bibliographic Details
Main Authors: Taher Al-Shehari, Muna Al-Razgan, Taha Alfakih, Rakan A. Alsowail, Saravanan Pandiaraj
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Anomaly detection
dataset imbalance issue
insider threat detection
isolation forest
machine learning
Online Access:https://ieeexplore.ieee.org/document/10290890/

Internet

https://ieeexplore.ieee.org/document/10290890/

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