Real Time Intrusion Detection System using Machine Learning
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-Today, world has come closer due to rapid increase internet. As technology has been developed many threats are emerged for the data security which is not at all good for sensitive data transactions, but as we know that the network security also posses equal importance in the computer infrastructure. Because of the intruders the security of the network has become serious problem. Thus to overcome this we are proposing this paper which is based on machine learning algorithm for intrusion detection using Naïve Bayesian Classifier, which is based on probabilistic model. This algorithm performs balance detections and keeps false positive rate at acceptable level for different types of real time networking attacks. In this, the system is trained by arranging the data attributes in a characterised format which eliminates the redundancy resulting in the reduction
[1] N. Srinivasan,et al. Using Random Forests for Network-based Anomaly detection at Active routers , 2008, 2008 International Conference on Signal Processing, Communications and Networking.
[3] Mehdi MORADI,et al. A Neural Network Based System for Intrusion Detection and Classification of Attacks , 2004 .