Hiroki Shimokubo’s research while affiliated with Nagoya University and other places

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Publications (2)


Personal Identification Through Pedestrians’ Behavior
  • Article

October 2018

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29 Reads

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4 Citations

The Review of Socionetwork Strategies

Xuanang Feng

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Hiroki Shimokubo

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Eisuke Kita

This article focuses on a new approach for personal identification by exploring the features of pedestrian behavior. The recent progress of a motion capture sensor system enables personal identification using human behavioral data observed from the sensor. Kinect is a motion sensing input device developed by Microsoft for Xbox 360 and Xbox One. Personal identification using the Microsoft Kinect sensor (hereafter referred to as Kinect) is presented in this study. Kinect is used to estimate body sizes and the walking behaviors of pedestrians. Body sizes such as height and width, and walking behavior such as joint angles and stride lengths, for example, are used as explanatory variables for personal identification. An algorithm for the personal identification of pedestrians is defined by a traditional neural network and by a support vector machine. In the numerical experiments, pictures of body sizes and the walking behaviors are captured from fifteen examinees through Kinect. The walking direction of pedestrians was specified as 0°, 90°, 180°, and 225°, and then the accuracies were compared. The results indicate that identification accuracy was best when the walking direction was 180°. In addition, the accuracy of the vector machine was better than that of the neural network.


Citations (1)


... Telephone conversation is considered as one of the most concerning privacy and security issues because it involves with users' personal information, such as user identification [1], financial information [2], passwords To address these challenges, in this paper, we propose Vibphone, a new side-channel attacking method exploiting a built-in zero-permission accelerometer to eavesdrop on telephone conversations as illustrated in Fig. 1. We have validated that smartphone accelerometers are sensitive to SIV signals, and the device diversity does have a decisive impact on the performance of Vibphone (see Section 3). ...

Reference:

Towards Device Independent Eavesdropping on Telephone Conversations with Built-in Accelerometer
Personal Identification Through Pedestrians’ Behavior
  • Citing Article
  • October 2018

The Review of Socionetwork Strategies