In this paper, we extend the context of subsumption anomalies and introduce additional types of anomalies that may be present in the KBS. The goal of this ...

Classifying and detecting anomalies in hybrid knowledge-based systems · Contents. Decision Support Systems. Volume 21, Issue 4 · NEXT ARTICLE. Verification of ...

Mar 8, 2022 · The present research is based on the implementation of one-class classifiers to detect anomalies in two industrial systems.

Nov 23, 2023 · This research paper proposes a hybrid feature selection strategy to address the challenges of network anomalies and malicious traffic detection.

Jul 29, 2024 · The proposed artificial intelligence-based intrusion detection system for botnet attack classification is robust, accurate, and exact. ... anomaly.

Oct 10, 2023 · Assessing the Impact of a Supervised Classification Filter on Flow-based Hybrid Network Anomaly Detection ... Hybrid Intrusion Detection System ...

Jun 5, 2023 · Researchers have proposed a method using semi-supervised learning to identify network anomalies and then using supervised learning to classify ...

Jul 22, 2022 · Generally, k-nearest neighbours (kNN) anomaly detection schemes are classified into two categories: density-based and distance-based schemes [25] ...

Mar 2, 2021 · In this paper, we have developed a hybrid anomaly detection method named DT-SVMNB that cascades several machine learning algorithms.