Detection of Network Intrusions using Machine
Learning
Journal:
GRENZE International Journal of Engineering and Technology
Authors:
Ruthvik V, Keshav Mittal, Manasa U Hegde, K Suhas, Annapurna D
Volume:
6
Issue:
2
Grenze ID:
01.GIJET.6.2.13
Pages:
151-153
Abstract
The aim of this project is to design and develop a software solution intended for
enterprises to use to detect and classify intrusions and abnormalities in their network. If any
such anomalies are detected, a designated administrator is notified to facilitate appropriate
action. Machine learning is used to detect any such anomalies in the enterprise network.
Our focus is on detecting and classifying DoS attacks.