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Evaluation of Software PUF Based on Gyroscope

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Information Security Practice and Experience (ISPEC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11879))

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Abstract

The Physically Unclonable Function (PUF), which extracts a unique device identification based on variations in manufacturing processes, has recently attracted attention. IoT devices, including sensor monitors and wearables, have come into widespread use, and various kinds of devices have access to a range of services. Device authentication and management of key to encryption communication data are essential for a secure service. We can realize secure authentication based on device identification extracted by a PUF. For example, PUF is used as a key generator to avoid storing the encryption key in a device. However, existing PUFs require dedicated hardware or software (driver) to extract device identification. Thus, it may not be possible to apply existing PUFs to IoT devices in a situation where there are a variety of devices and many device manufacturers. We can use characteristic values of existing sensors in an IoT device as an alternative to PUF. In this paper, we expand an existing software PUF based to support characteristic values extract from a gyroscope, and evaluate the entropy and robustness. We found that the same device identifier can be reliably extracted from a gyroscope even under conditions of high and low temperature, and low-pressure. No changes in the characteristic values of the gyroscope due to degradation with age were found over a wearing period exceeding than three years. The device identifier has up to 81.2 bits entropy with no error-correcting mechanism. It has up to 57.7 bits entropy when error-correction of one bit is applied to each characteristic value by a Fuzzy extractor.

A. Yoshimura—He currently belongs to TDC SOFT Inc.

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Author information

Authors and Affiliations

  1. KDDI Research, Inc., 2–1–15 Ohara, Fujimino, Saitama, 356–8502, Japan

    Kazuhide Fukushima & Shinsaku Kiyomoto

  2. Tamagawa University, 6–1–1 Tamagawagakuen, Machida, Tokyo, 194–8610, Japan

    Ayumu Yoshimura & Norikazu Yamasaki

Authors
  1. Kazuhide Fukushima
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  2. Ayumu Yoshimura
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  3. Shinsaku Kiyomoto
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  4. Norikazu Yamasaki
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Corresponding author

Correspondence to Kazuhide Fukushima .

Editor information

Editors and Affiliations

  1. Multimedia University, Malacca, Malaysia

    Swee-Huay Heng

  2. University of Malaga, Malaga, Spain

    Javier Lopez

A Implementation on Wear OS Device

A Implementation on Wear OS Device

Fig. 6.
figure 6

Acquisition of maximum and minimum values of the gyroscope [9]

Full size image

Figure 6 shows a sample implementation designed to acquire the maximum and minimum values of the gyroscope in a wearable device with Wear OS. The fields maxX, minX, maxY, minY, maxZ, and minZ are fields that store the tentative maximum and minimum values of the angular velocities around the x, y and z-axes. The method onSensorChanged is called when the sensor values have changed. We retrieve the event from the gyroscope by using the if statement. The angular velocities around the x, y, and z-axes are stored in the values array. The same code where Sensor.TYPE_GYROSCOPE is replaced with Sensor.TYPE_ACCELEROMETER can acquire the maximum and minimum values of accelerations along each axis.

The software PUF based on a gyroscope needs to set the highest sampling frequency on the sensors so that we can efficiently acquire the maximum and minimum values. We can set the sampling frequency through the registerListener method in Android. The method registers SensorEventListener that is used to receive notifications from the SensorManager when the sensor values have changed. The notification frequency is highest, and the period is a few milliseconds if SENSOR_DELAY_FASTEST is passed to the method.

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Fukushima, K., Yoshimura, A., Kiyomoto, S., Yamasaki, N. (2019). Evaluation of Software PUF Based on Gyroscope. In: Heng, SH., Lopez, J. (eds) Information Security Practice and Experience. ISPEC 2019. Lecture Notes in Computer Science(), vol 11879. Springer, Cham. https://doi.org/10.1007/978-3-030-34339-2_13

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  • DOI: https://doi.org/10.1007/978-3-030-34339-2_13

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  • Online ISBN: 978-3-030-34339-2

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