With the fast development of PC utilization and PC network, the security of the PC framework has turned out to be very significant. Businesses are looking for consistently new sorts of assaults. As the danger turns into a genuine chapter year by year, interruption discovery advancements are essential for organization and PC security. An assortment of interruption recognition approaches be available to determine this severe condition; in any case, the fundamental problem is execution. It is imperative to increment the discovery rates and lessen bogus alert rates in the space of interruption recognition. To recognize the interruption, different methodologies have been created and proposed over the most recent decade. This paper effectively compares the accuracy of different classification algorithms, like algorithms like Support Vector Machine (SVM), Naive Bayes, KNN, Decision Tree[15]. This study aims to perform a comparative analysis of these different machine learning algorithms on datasets available to predict which model best suits intrusion detection.