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A Novel Approach to True Random Number Generation in Wearable Computing Environments Using MEMS Sensors

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Book cover Information Security and Cryptology (Inscrypt 2014)

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Abstract

Micro Electro Mechanical Systems (MEMS) sensors (accelerometer, gyroscope, and compass) offer a practical approach for true random number generation. Entropy values of 0.99 close to theoretical value of 1, and large Kullback-Leibler distances were obtained in this study [1]. The main contribution of this work was the generation of high quality random number strings, when the MEMS sensor was at complete rest, a configuration in which these sensors were heretofore considered to be inadequate. This was accomplished by using the initial noise in the sensing mechanisms for the MEMS sensors. The compass output stream passed the highest number of NIST Tests; 11/15 and 14/15 under stationary and complete motion, respectively [2–4]. Short burst (<1 s) strings passed 13 out of 15 NIST tests, and applying the Barak-Impagliazzo-Wigderson recursive extractor led to successful results in all 15 NIST tests. Interleaving MEMS output with audio resulted in a string that passed 14 out of 15 NIST tests.

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Acknowledgments

The authors would like to thank Professor John Steinberger for helpful discussions and support through the summer internship. This work was performed at Tsinghua University, Institute for Interdisciplinary Information Sciences, Beijing, China and their support is greatly appreciated. The authors also appreciate the support of Cameron Ballingall and InvenSense Inc., which provided the MEMS sensors used in this study. The authors would also like to thank the reviewers for their comments and suggestions.

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Authors and Affiliations

  1. Institute for Interdisciplinary Information Sciences, Tsinghua University, FIT Building, 1-208, Beijing, 100084, China

    Neel Bedekar

  2. Airbus Industrie, Xylem Building, Mahadevapura, Bangalore, 560038, India

    Chiranjit Shee

Authors
  1. Neel Bedekar
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  2. Chiranjit Shee
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Correspondence to Neel Bedekar .

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Editors and Affiliations

  1. SKLOIS, Institute of Engineering, Chinese Academy of Sciences, Beijing, China

    Dongdai Lin

  2. Computer Science Department, Columbia University, New York, New York, USA

    Moti Yung

  3. Infocomm Security Department, Institute for Infocomm Research, Singapore, Singapore

    Jianying Zhou

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Bedekar, N., Shee, C. (2015). A Novel Approach to True Random Number Generation in Wearable Computing Environments Using MEMS Sensors. In: Lin, D., Yung, M., Zhou, J. (eds) Information Security and Cryptology. Inscrypt 2014. Lecture Notes in Computer Science(), vol 8957. Springer, Cham. https://doi.org/10.1007/978-3-319-16745-9_29

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  • DOI: https://doi.org/10.1007/978-3-319-16745-9_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16744-2

  • Online ISBN: 978-3-319-16745-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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