
Security and privacy of a system is compromised, when an intrusion happens. Intrusion Detection System (IDS) plays vital role in network security as it detects various types of attacks in network. Implementation of an IDS is distinguishes between the traffic coming from clients and the traffic originated from the attackers or intruders, in an attempt to simultaneously mitigate the problems of throughput, latency and security of the network. Data mining based IDS can effectively identify intrusions. The proposed scheme is one of the recent enhancements of naive bayes algorithm. It solves the problem of independence by averaging all models generated by traditional one dependence estimator and is well suited for incremental learning. Empirical results show that proposed model based on SADE is efficient with low FAR and high
By DR. Anamika Sharma | Prof. Arun Jhapate" An Intrusion Detection System Using Singular Average Dependency Estimator in Data Mining"
Paper URL: http://www.ijtsrd.com/papers/ijtsrd18166.pdf
Direct URL: http://www.ijtsrd.com/computer-science/data-miining/18166/an-intrusion-detection-system-using-singular-average-dependency-estimator-in-data-mining/anamika-sharma
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