A Survey on Machine Learning Techniques in Network Intrusion Detection System
B. Ida Seraphim, Shreya Palit, Kaustubh Srivastava, Eswaran Poovammal · 2018
Huge amounts of data is being generated every second due to technological development and innovations coming out in the market. Social Networking and the cloud computing boom in this technological world is generating large amounts of data every second. Streaming data, a technical term was devised to represent the constant generation of data on the World Wide Web. These data are constantly putting pressure and checking its limits on the current Intrusion Detection System(IDS). These systems are a device or software applications that keep a track log as well as monitors any malicious activity happening on the network. In order to detect and then prevent network security breaches in the system, many machine learning algorithms have been applied to the data generated in order to recognize any pattern in anomaly actives that are happening over the network system.