Published Paper Details:

The aim of this project helps to develop an application to find the type of attack that occurred on the system and to detect the intruders by using Intrusion Detection System. Previously various machine learning (ML) techniques are applied on the IDS and tried to improve the results on the detection of intruders and to increase the accuracy of the IDS. This paper has proposed an approach to develop efficient IDS by using the principal component analysis (PCA) and the random forest classification algorithm. Where the PCA will help to organise the dataset by reducing the dimensionality of the dataset and the random forest will help in classification. Results obtained states that the proposed approach works more efficiently in terms of accuracy as compared to other techniques like SVM, Naive Bayes, and Decision Tree. The IDS acts as a network level defence to secure a system. IDS mainly used for security purpose to find the threats or malicious activities and also for identifying the type of attack on the system.