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An intelligent ensemble of long-short-term memory with genetic algorithm for network anomaly identification.

, , , , , and . Trans. Emerg. Telecommun. Technol., (2022)

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An integrated intrusion detection system using correlation-based attribute selection and artificial neural network., , , , and . Trans. Emerg. Telecommun. Technol., (2021)Identification of Phishing Attack in Websites Using Random Forest-SVM Hybrid Model., , , and . ISDA (2), volume 941 of Advances in Intelligent Systems and Computing, page 120-128. Springer, (2018)sv(M)kmeans - A Hybrid Feature Selection Technique for Reducing False Positives in Network Anomaly Detection., , and . COMAD, page 109-112. Computer Society of India, (2014)Parallelization of Machine Learning Models for Credit Card Fraud Detection., , , , and . Int. J. Syst. Syst. Eng., (2023)Identification of Botnet Attacks Using Hybrid Machine Learning Models., , , and . HIS, volume 1179 of Advances in Intelligent Systems and Computing, page 249-257. Springer, (2019)Revolutionizing Malware Detection: Feature-Based Approach for Targeting Diverse Malware Categories., and . ICCST, page 1-5. IEEE, (2023)Analysis on Improving the Performance of Machine Learning Models Using Feature Selection Technique., , , and . ISDA (2), volume 941 of Advances in Intelligent Systems and Computing, page 69-77. Springer, (2018)Performance Analysis of Single- and Ensemble-Based Classifiers for Intrusion Detection., , and . SocProS (2), volume 1057 of Advances in Intelligent Systems and Computing, page 759-770. Springer, (2018)An Integrated Intrusion Detection System for Credit Card Fraud Detection., , and . ACITY (1), volume 176 of Advances in Intelligent Systems and Computing, page 55-60. Springer, (2012)An intelligent ensemble of long-short-term memory with genetic algorithm for network anomaly identification., , , , , and . Trans. Emerg. Telecommun. Technol., (2022)