Effectiveness Evaluation of Random Forest, Naive Bayes, and Support Vector Machine Models for KDDCUP99 Anomaly Detection Based on K-means Clustering by Zhang Majun

“…Naïve Bayes (NB). and Support Vector Machine (SVM) with the goal to boost the accuracy of predicting network intrusions. In tins paper. K-means clustering technique is applied as a preprocessing step to enhance the overall quality of network intrusion detection and maximize the accuracy of the network security measures. …”
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A Dynamic Intrusion Detection System Based on Multivariate Hotelling’s T2 Statistics Approach for Network Environments by Aneetha Avalappampatty Sivasamy, Bose Sundan

“…Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling’s T2 method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. …”
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Network Packet Sniffer: A Case Study of Kabale University. by Mugarurebye, Shawn, Gumoshabe, Rebecca

“…Thus, it plays a crucial and essential role in dealing with network intrusion detection and unwanted traffic control. …”
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An intrusion detection model based on Convolutional Kolmogorov-Arnold Networks by Zhen Wang, Anazida Zainal, Maheyzah Md Siraj, Fuad A. Ghaleb, Xue Hao, Shaoyong Han

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Trust in Intrusion Detection Systems: An Investigation of Performance Analysis for Machine Learning and Deep Learning Models by Basim Mahbooba, Radhya Sahal, Wael Alosaimi, Martin Serrano

“…Two datasets are used to classify the IDS attack type, including wireless sensor network detection system (WSN-DS) and KDD Cup network intrusion dataset. A detailed comparison of the eight techniques’ performance using all features and selected features is made by measuring the accuracy, precision, recall, and F1-score. …”
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A two-tier optimization strategy for feature selection in robust adversarial attack mitigation on internet of things network security by Kashi Sai Prasad, P Udayakumar, E. Laxmi Lydia, Mohammed Altaf Ahmed, Mohamad Khairi Ishak, Faten Khalid Karim, Samih M. Mostafa

“…Numerous research works were keen to project intelligent network intrusion detection systems (NIDS) to avert the exploitation of IoT data through smart applications. …”
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An Evaluation of Variational Autoencoder in Credit Card Anomaly Detection by Faleh Alshameri, Ran Xia

“…The anomaly can occur in many forms, such as fraudulent credit card transactions, network intrusions, and anomalous imageries or documents. …”
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