• P.Kanagavalli
• Dr.V.Karthikeyani

In recent day’s era the security of WSN (Wireless Sensor Network) is of big concern. In previous years, a dramatic enhancement issues in the number of attacks, intrusion detection field and it becomes the mainstream of data assurance. Sensors nodes are used in WSN with the onboard processors that manages and monitors the environment in the a particular area. They are connected to the Base Station which acts as a processing unit in the WSN System. In WSN, data mining is the process of extracting model and pattern that are application oriented with possible accuracy from rapid flow of data. Because of their special characteristics, and limitations of the WSNs, the traditional data mining approaches are not directly applicable to WSNs. A widespread analysis of different pre-existing data mining techniques adopted for WSNs are examined with different classification, evaluation approaches in this paper. Finally, a few research challenges to adopt data mining methods in WSNs are also pointed out. A general concept of how traditional data mining techniques are improved to attain better performance in a wireless sensor network.

Wireless Sensor Network, NSL-KDD data set, Random Forest algorithm, C4.5 algorithm, SVM algorithm and CART algorithm

"COMPARATIVE ANALYSIS OF DATA MINING ALGORITHMS IN WIRELESS SENSOR NETWORK’S SECURITY SYSTEM USING RANDOM FOREST, C4.5, SVM AND CART", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.156-163, March-2023, Available :http://www.jetir.org/papers/JETIRFV06029.pdf

"COMPARATIVE ANALYSIS OF DATA MINING ALGORITHMS IN WIRELESS SENSOR NETWORK’S SECURITY SYSTEM USING RANDOM FOREST, C4.5, SVM AND CART", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. pp156-163, March-2023, Available at : http://www.jetir.org/papers/JETIRFV06029.pdf