Abstract
The purpose of this chapter is to describe a new approach to recognize the identity of a person through analyzing the behavioral biometrics in Wi-Fi signals and their potential application prospects. A solid understanding of processing Wi-Fi signals helps to interpret solid information and problem statement on identity recognition through Wi-Fi signals. The ubiquitous and temporal features of Wi-Fi signals are the basis of recognition and localization. We introduce a new paradigm on how to use Wi-Fi signals to identify the human in the open environment. We proposed Wide, a Wi-Fi signal-based human identity recognition system. First, we describe the components of Wide and how it works in detail. Through collecting CSI (channel state information) profiles, Wide is able to recognize the human identity through sampling and extracting features of the received Wi-Fi signals. Then, to reduce the storage overhead while guaranteeing high recognizing accuracy, principal component analysis (PCA) technique is used. Finally, test-bed experiments are conducted to show the performance of Wide, indicating that Wide can quickly recognize people in a high accuracy.
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