Mitigation of Attacks via Improved Network Security in IoT Network using Machine Learning
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Abstract
In this paper, we develop a support vector machine (SVM) based attack mitigation technique from the IoT network. The SVM aims to classify the features related to the attacks based on pre-processed and feature extracted information. The simulation is conducted in terms of accuracy, precision, recall and f-measure over KDD datasets. The results show that the proposed SVM classifier obtains high grade of classification accuracy in both training and testing datasets.
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