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Behavioral Biometrics Based on Human-Computer Interaction Devices

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Biometric-Based Physical and Cybersecurity Systems

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.

The chapter starts with the definition of Wi-Fi signals and CSI (channel state information) and behavioral biometrics-related applications. Particular emphasis is placed on the characteristic of the CSI, which indicates that CSI can be used for recognizing the identity of people. Then we highlight our objective and demonstrate our design in detail. At last, experiments are conducted through collecting, analyzing, and processing Wi-Fi signals to recognize the identity of people, revealing that the proposed scheme can recognize people with promising accuracy in a short time.

This chapter is structured as follows. Section 1 focuses on research background in behavioral biometrics and illustrations on characteristics of key technologies. Section 2 gives a brief overview on related achievement in this research field. Section 3 looks at the essence of related theory and behavioral biometric recognition methods. Section 4 deals with experimental installations and configurations. Section 5 analyzes the experimental results and discusses the potential features of our scheme. Section 6 concludes this chapter and outlines future research trends in Wi-Fi signal topics.

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Author information

Authors and Affiliations

  1. School of Software, Dalian University of Technology, Dalian, China

    Chi Lin

  2. Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian, China

    Chi Lin

  3. Department of Computer and Information Science, Fordham University, Bronx, NY, USA

    Mohammad S. Obaidat

Authors
  1. Chi Lin
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  2. Mohammad S. Obaidat
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Correspondence to Chi Lin .

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Editors and Affiliations

  1. ECE Department, Nazrabayev University, Astana, Kazakhstan

    Mohammad S. Obaidat

  2. Department of Electrical and Computer Engineering, University of Victoria – UVIC, Victoria, BC, Canada

    Issa Traore

  3. Department of Computer Science, Ryerson University, Toronto, ON, Canada

    Isaac Woungang

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Lin, C., Obaidat, M.S. (2019). Behavioral Biometrics Based on Human-Computer Interaction Devices. In: Obaidat, M., Traore, I., Woungang, I. (eds) Biometric-Based Physical and Cybersecurity Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-98734-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-98734-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98733-0

  • Online ISBN: 978-3-319-98734-7

  • eBook Packages: EngineeringEngineering (R0)

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