Rogue WiFi Detection Based on CSI Multi-feature Fusion

At present, using WiFi to access the Internet has become a mainstream way. However, through research on wireless network security, it is found that attackers forge the mac address or SSID of legitimate users to obtain illegal information. This method is difficult to be detected by traditional network security mechanisms. In this article, we propose a new security mechanism that uses multiple features extracted from Channel State Information (CSI) which are irrelevant to the environment for fusion, and uses a minimum discriminant criterion for classification and discrimination to reject rogue WiFi connections. We found that the Carrier Frequency Offset (CFO) and nonlinear phase error extracted from CSI are stable in time and space. Experiments on a large number of WiFi devices show that this mechanism can reliably detect rogue WiFi connections, with an average recognition rate over 96%. At the same time, through comparing the recognition effect between before and after the feature fusion, we verify the superiority of the fusion method, and provides a reliable basis for the identification of rogue WiFi.