Intrusion Detection System using ML

Intrusion Detection System using ML

Author Name : Prabhdeep Singh, Aditya Bhagawan Ghadge, Mohammed Faizan, Kola Sai Chakradhar, Ayush Mishra, Sreevardhan Reddy Soma, Chitteni Sai Sanjay

ABSTRACT

The need to secure networks has increased as the number of people connecting to the network are increasing rapidly and using networks for storing or accessing critical information. In this paper we have assessed and compared various machine learning algorithm and then propose a system based on the best performing algorithm. Our system is an intrusion prediction system with low error rate and can be implemented in real world. The dataset used in this project would be the database that contains set of data to be assessed, which includes a wide variety of intrusions simulated in a military network environment. The dataset contains mainly the normal state, DDoS and some other attacks. The system will not only predict a malicious network but also point to exactly under which type of attack the network is subjected to.

Key words: learning, decision table, random forest, network intrusion.