Network Based Intrusion Detection System Using Weighted Product Model (WPM)

A security technology called a network-based intrusion detection system (NIDS) was created to safeguard computer networks against unauthorised access and criminal activity. This technology works by analysing network traffic, spotting potential risks, and informing administrators of any possible incursions or attacks. NIDS research ensures that intrusion detection systems are built to minimise the gathering and storage of sensitive data by taking into account the value of privacy and data protection .In general, network-based intrusion detection system research has a major impact on how well these security measures operate, how efficiently they perform, and how adaptable they are.By addressing the evolving challenges posed by cyber threats, NIDS research helps organizations enhance their network security posture, protect sensitive information, and defend against potential intrusions and attacks." The weighted product model (WPM), a multi-criteria decision-making (MCDM) technique, is used to evaluate and rank solutions based on a variety of distinct criteria. It provides a methodical approach to decision-making by considering the relative importance of each attribute and the performance of other solutions in relation to those criteria. The WPM normalises the data, weights the criteria, and gives a weighted score for each alternative. The option with the greatest score is regarded as the ideal option. The weighted product model offers a structured framework for making decisions by taking into account many factors and their varying degrees of importance. It enables decision-makers to assess and contrast options using a wide range of criteria, resulting in more informed and unbiased choices. It's crucial to check nonetheless that the model's weights and normalisation techniques appropriately capture the decision-maker's preferences as well as the features of the choice problem.J48, Random Forest, JRIP, RIDOR, PART. The definition of true positive, false positive, true negative and false negative rates has already been established. These metrics for measuring the effectiveness of classification algorithms, anomaly detection systems, and binary decision-making processes are accurately presented. As can be seen from the results, J48 received the highest rank, while PART received the lowest .In order to increase the security of computer networks, network-based intrusion detection systems (NIDS) are essential. They provide real-time monitoring and analysis of network traffic to identify suspected breaches and malicious activities, enabling appropriate action to be taken. However, it is important to recognize that NIDS can have limitations and are not infallible.