Random Forest Classifier Based Network Intrusion Detection System

Abstract

In today's digital world, we all use the Internet and connect to a network, but all the data we send or receive, is safe? Some kind of attack is present in network packets that might access the computer's private information to the hacker. We cannot see and tell whether a network is safe to connect with or not, so we made a Network Intrusion Detection Model predict whether these network packets are secure or some attack is there on the package. We use Random Forest Classifier to obtain the maximum accuracy. To test our model in real-time, we have created a packet sniffer that would sniff out network packets, convert them into required features, and then try it in our model to predict the legitimacy of the network packet.