Oct 19, 2024 · Machine Learning (ML)-based network intrusion detection systems bring many benefits for enhancing the cybersecurity posture of an organisation.
Oct 21, 2024 · This work asserts a novel Hybrid Adaptive Ensemble for Intrusion Detection (HAEnID), an innovative and powerful method to enhance intrusion detection.
Oct 22, 2024 · In this paper, we offer an explainable ensemble DL-based IDS to improve the transparency and robustness of DL-based IDSs in IIoT networks.
Nov 23, 2022 · To assist them in this task, network intrusion detection systems (NIDSs) monitor the network and raise alarms when they identify suspicious ...
Jun 14, 2023 · The experimental results show that the framework can improve the efficiency of the Intrusion Detection System, achieving an accuracy rate of 0.9863.
Sep 13, 2024 · Intrusion detection in network systems through hybrid supervised and unsupervised machine learning process: a case study on the iscx dataset.
Oct 23, 2023 · In order to protect systems and networks from malicious actions that can bypass security boundaries, Intrusion Detection Systems (IDSs) are.
Nov 7, 2023 · This research presents a comprehensive Systematic Review of the Literature where works related to intrusion detection with ensemble learning ...
Missing: Explainability | Show results with:Explainability
In this survey, we present a comprehensive study of different XAI-based intrusion detection systems for industry 5.0, and we also examine the impact of ...
A comparative study of explainable ensemble learning and logistic ...
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Feb 10, 2024 · This study aims to compare the predictive performance of ensemble learning (EL) models with LR for in-hospital mortality in the ED.
Missing: Intrusion | Show results with:Intrusion