A Comparability Study of Intrusion Detection System using Data Mining Techniques


A Comparability Study of Intrusion Detection System using Data Mining Techniques

K. Raja, Dr. M. Lilly Florence, Dr. D. Swamydoss

K. Raja, Dr. M. Lilly Florence, Dr. D. Swamydoss "A Comparability Study of Intrusion Detection System using Data Mining Techniques" Published in International Journal of Trend in Research and Development (IJTRD), ISSN: 2394-9333, Special Issue | PCIT-15 , December 2015, URL: http://www.ijtrd.com/papers/IJTRD1300.pdf

The Main objective of this paper is to avoid the intrusion using data mining techniques with help of multi agents. Data mining is a discovery process that allows users to understand the substance of and the relationships between, their data. Data mining uncovers patterns and rends in the contents of this information. Intrusion detection systems have been used along with the data mining techniques to detect intrusions. In this work we aim to use data mining techniques including classification tree and support vector machines for intrusion detection. To meet the challenges of both efficient learning (mining) and real-time detection, we propose an agent based architecture for intrusion detection systems where the learning agents continuously compute and provide the updated (detection) models to the detection agents. Intrusion detection is therefore needed as another wall to protect computer systems.

Data Mining, Intrusion Detection System (IDS), Preprocessing, Decision Tree, Clustering Techniques, Intrusion Detection Technique.


Special Issue | PCIT-15 , December 2015

2394-9333

IJTRD1300
pompy wtryskowe|cheap huarache shoes| cheap jordans|cheap jordans|cheap air max| cheap sneaker cheap nfl jerseys|cheap air jordanscheap jordan shoes
cheap wholesale jordans