A network intrusion is an unauthorized operation of a computer network. The goal of a network access program is to protect computer networks from unauthorized users, including internal users. Create a local network discovery. This is a predicted form that distinguishes between "high quality" or typical associations and "terrible" associations, sometimes called intruders or attacks. The purpose was to evaluate accessibility results. We also concentrated on machine learning-based classification to facilitate acquires greatest training and testing, to access our strategy for using currently available technologies. To generate various classification models, used varieties machine-learning based techniques and comparing each other for detecting best fit model for the computer networks with respect to time and accuracy. Based on comparisons with six different machine learning algorithms used to categories attacks, it is feasible to determine the originality of the proposed IDT by the fact that it utilizes the best machine learning method possible to fit into a high performance IDT.