Abstract
Abstract: It's crucial to have reliable intrusion detection systems. a cutting-edge method of machine learning-based intrusion detection. Our solution uses cutting-edge algorithms to detect and eliminate any threats instantly, acting as a preventative measure against a wide range of cyberattacks. Since the model has been trained on a large number of datasets, it can eventually strengthen network security by evolving and adapting to new threats. Naive Bayes (NB) classifiers and correlation-based feature selection (CFS) methods are used to reduce the amount of data. For attack classification, the Intrusion Detection System recommends using an Instance-Based Learning algorithm (IBK) in combination with a Multilayer Perceptron (MLP).
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