Data Set Construction and Performance Comparison of Machine Learning Algorithm for Detection of Unauthorized AP
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With the frequent use of Wi-Fi and hotspots that provide a wireless Internet environment, awareness and threats to wireless AP security are steadily increasing. Especially when using unauthorized APs in company, government and military facilities, there is a high possibility of being subjected to various viruses and hacking attacks. Therefore, it is necessary to detect and detect authorized APs and unauthorized APs. In this paper, to detect authorized APs and unauthorized APs, the characteristics of RTT (Round Trip Time) values are set as dataset and each machine learning algorithm SVM (Support Vector Machine), J48 (C4.5), KNN (K nearest neighbors), and MLP (Multilayer Perceptron).
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