Gait-Based Authentication for Smart Locks Using Accelerometers in Two Devices

  • Kazuki Watanabe
  • Makoto Nagatomo
  • Kentaro Aburada
  • Naonobu Okazaki
  • Mirang ParkEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1036)


Smart locks can be opened and closed electronically. Fingerprint or face authentication is inconvenient for smart locks because it requires the user to stop for several seconds in front of the door and remove certain accessories (e.g., gloves, sunglasses). This study proposes a user authentication method based on gait features. Conventional gait-based authentication methods have low identification accuracy. The proposed gait-based authentication method uses accelerometers in a smartphone and a wearable device (i.e., smartwatch). We extracted 31 features from the acquired acceleration data and calculated identification accuracy for various machine-learning algorithms. The highest accuracy was 95.3%, obtained using random forest. We found that the maximum interval, minimum interval, and minimum value had the highest contributions to identification accuracy, and variance, median, and standard deviation had the lowest contributions.



This work was supported by JSPS KAKENHI Grant Numbers JP17H01736, JP17K00139.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Kazuki Watanabe
    • 1
  • Makoto Nagatomo
    • 1
  • Kentaro Aburada
    • 2
  • Naonobu Okazaki
    • 2
  • Mirang Park
    • 1
    Email author
  1. 1.Kanagawa Institute of TechnologyAtsugiJapan
  2. 2.University of MiyazakiMiyazakiJapan

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