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Phonetics-Based Parallel Privacy Preserving Record Linkage

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Book cover Advances on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 13))

Abstract

We live in an era characterized by the abundance of data, often conveying personal information. Linking this kind of data is useful for a variety of applications, raising, however privacy concerns. To address this issue, privacy preserving record linkage has emerged, with techniques aiming at revealing to the matching parties only the actually matching records. Since the linking process usually involves large volumes of data, it is evident that such procedures could benefit from outsourcing computation to cloud infrastructures taking advantage of parallel computing platforms, such as Apache Spark. In this paper, we extend a phonetic codes based method for privacy preserving string matching, by designing a new protocol specifically tailored to operate in parallel in the cloud, employing the map reduce model. We theoretically analyze its characteristics and empirically assess its performance, comparing it with the corresponding sequential algorithm.

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Notes

  1. 1.

    https://okeanos.grnet.gr/home/.

  2. 2.

    http://dl.ncsbe.gov/index.html?prefix=data/.

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Authors and Affiliations

  1. University of Macedonia, Thessaloniki, Greece

    Alexandros Karakasidis & Georgia Koloniari

Authors
  1. Alexandros Karakasidis
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  2. Georgia Koloniari
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Corresponding author

Correspondence to Alexandros Karakasidis .

Editor information

Editors and Affiliations

  1. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

  2. Open University of Catalonia, Barcelona, Spain

    Santi Caballé

  3. Fukuoka Institute of Technology (FIT), Fukuoka, Japan

    Leonard Barolli

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Karakasidis, A., Koloniari, G. (2018). Phonetics-Based Parallel Privacy Preserving Record Linkage. In: Xhafa, F., Caballé, S., Barolli, L. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-69835-9_16

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  • DOI: https://doi.org/10.1007/978-3-319-69835-9_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69834-2

  • Online ISBN: 978-3-319-69835-9

  • eBook Packages: EngineeringEngineering (R0)

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