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Risk Assessment for Privacy Protection of Information Literacy Beginners in Big Data Era

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Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 7))

Abstract

The utilization of big data by companies such as Facebook and Google is increasing, and the possibility of producing an unprecedented new service and system using such data is expected. However, the issue of privacy protection is a concern in the utilization of big data. Consequently, risk assessment in connection with the privacy protection is an important issue, especially the privacy of information literacy beginners (people less familiar with data security). This paper explores the issue of privacy protection of information literacy beginners in big data utilization. We first conducted a risk assessment in a qualitative analysis of privacy protection from a comprehensive viewpoint. As a result, 29 risk factors were extracted, and countermeasures were proposed. The important elements of the proposed measures were determined to be strengthening the security of terminals and thoroughly defining terminal use rules. Next, we described a quantitative evaluation of these risk factors obtained as a result of the qualitative analysis. Specifically, a risk value based on a formula was calculated for each risk factor. On the basis of the risk value, the effect of the countermeasures on the risks was then quantitatively evaluated. It was shown that the countermeasures can reduce their corresponding risk factors by about 49%. The results of this study are expected to contribute to the safe and secure use of big data.

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Acknowledgments

This work was supported by the Japan Society for the Promotion of Science (JSPS, KAKENHI Grant Number 15H02783).

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Correspondence to Shigeaki Tanimoto .

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Tanimoto, S., Totsuka, S., Iwashita, M., Seki, Y., Sato, H., Kanai, A. (2018). Risk Assessment for Privacy Protection of Information Literacy Beginners in Big Data Era. In: Barolli, L., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-65521-5_66

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  • DOI: https://doi.org/10.1007/978-3-319-65521-5_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65520-8

  • Online ISBN: 978-3-319-65521-5

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