The strategy for detecting suspicious behavior can be the following. Firstly, select initial suspicious data, misclassification data retention and combination ...
This publicly available dataset contains information related to Traffic Capture, Firewall Logs, Email, and user activities. They employed ML-based methods ...
In this paper, we propose a novel IoT network intrusion detection approach based on adaptive Particle Swarm Optimization Convolutional Neural Network (APSO-CNN) ...
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May 3, 2024 · Additionally, a data adjustment (DA) strategy was developed to change the weights of the majority and minority samples. Subsequently, the ...
Oct 28, 2024 · This study examines the formidable and complex challenge of insider threats to organizational security, addressing risks such as ransomware incidents.
Oct 30, 2023 · It employed a cost-sensitive data adjustment strategy to categorize the unbalanced real-world insider threat data, which only com- prised a ...
[PDF] Insider Detection Using Combination of Machine Learning and ... - ijeetc
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Sep 11, 2024 · “Data adjusting strategy and optimized XGBoost algorithm for novel insider threat detection model,” Journal of the Franklin. Institute, vol.
A generic algorithm was used to find the optimal HTTP features to help detect abnormal insider behaviours from normal behaviours. Although the study achieved ...
Sep 20, 2024 · This work seeks to explore the potential of the AdaBoost classifier in order to handle detection of insider threats within an organization. A ...
The advantage of employing self-supervised learning for insider threat detection lies in its potential ability to identify malicious insiders without the use of ...
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