Application of Machine Learning in Intrusion detection using a feedback System: Study

With the growth and expansion of network technologies, every corner of the world is now connected and people are using the Internet to a great extent. As an eternal truth, every growth brings many challenges along with it. Some challenges over the Internet are security, availability, speed, congestion, etc. Among all major threats, security is most important and must be dealt with a lot of attention and accuracy. Security measures applied must work on time (real-time) and must not cause a lot of delays in the processing of data. For security over the Internet, Intrusion Detection techniques are being used prominently. Intrusion Detection Systems (IDS) process every incoming and outgoing data packet from the system whether a particular machine or a network. Hence it requires working with huge of data that not only contains the information linked to security threats but can also learn from them and apply it for all future traffic. This work provides an IDS with machine learning to process large data of IP packets.