Application of Real Time Data Mining for Intrusion Detection Systems
The advances in computer technology and IT in the last few decades has led to an increased amount of information and data being generated and stored in various datacenters. Further the increased use of internet today, security of network systems has become more important as sensitive information is being stored and manipulated online. The use of Intrusion Prevention Systems (IPSs) and Intrusion Detection Systems (IDSs) has thus become a critical technology to help to protect these systems. This paper addresses the important and challenging issues of accuracy, efficiency and usability of application of real-time data mining to Intrusion Detection Systems using K-mean clustering algorithm.