Traditionally, it is considered that there is no sensitive information in the management frames and only the data frames need encryption protection in the initial 802.11 standard protocol, so no corresponding security mechanism is required in the management frames. But with the popularity of WLAN, the researchers realize that the lack of the management frames security mechanism can lead to many security problems. For example, an attacker can constantly transmit fake management frames to dissociate normal connection between the AP and the legitimate station. Therefore, the management frames security mechanism must be established. In this paper, we propose a topic model based method to realize the authentication of Wi-Fi management frames using the Channel State Information (CSI). CSI values have a strong correlation with location. That means CSI values between the AP and the legitimate station have significant distinction with the CSI values between the AP and the attacker. We utilize the topic model - an unsupervised machine learning method to extract features automatically from the collected CSI values. Extensive experiments are conducted to analysis the system performance. The experiments prove that topic model can better resist noise interference than the traditional method and achieve average 91% accuracy of the management frame authentication.
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