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Distributed L-diversity using spark-based algorithm for large resource description frameworks data

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Abstract

Privacy protection issues for resource description frameworks (RDFs) have emerged over the use of public government open data and the healthcare data of individuals. As these data may include personal information, they must undergo a de-identification process that deletes or replaces parts of the original data. To enable these protections, a method has been developed to apply k-anonymization to RDF data. However, sensitive RDF information anonymized using k-anonymization is not completely secure and is vulnerable to attacks. In this paper, we propose an l-diversity anatomy de-identification method that can overcome the limitations of k-anonymity and guarantee stronger privacy protection than k-anonymization. Further, as this data anonymization process is computationally time-intensive, we use Spark distributed computing to provide rapid de-identification to enhance its utility. We also propose l-diversity preservation for dynamically evolving RDF datasets. Experimental results show that our proposed distributed l-diversity algorithm processes the data more efficiently than conventional approaches.

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Acknowledgments

This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) supported program (IITP-2020-2018-0-01417) supervised by the IITP (Institute for Information & Communications Technology Planning & Evaluation); and by the Basic Science Research Program through NRF, funded by the Ministry of Education (No. NRF-2018R1D1A1B07048380).

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Authors and Affiliations

  1. Department of Computer Engineering, Hoseo University, Asan, 31499, Korea

    MinHyuk Jeon & Odsuren Temuujin

  2. Department of Management Information Systems, Jeju National University, Jeju, 63243, Korea

    Jinhyun Ahn

  3. School of Information Convergence, Kwangwoon University, Seoul, 01890, Korea

    Dong-Hyuk Im

Authors
  1. MinHyuk Jeon
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  2. Odsuren Temuujin
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  3. Jinhyun Ahn
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  4. Dong-Hyuk Im
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Contributions

MinHyuk Jeon and Dong-Hyuk Im conceived the problem and supervised the overall research; Jinhyun Ahn clarified some points that helped Dong-Hyuk Im to develop the algorithm; Odsuren Temuujin and MinHyuk Jeon implemented the algorithm and performed the experiments; MinHyuk Jeon, Odsuren Temuujin, and Dong-Hyuk Im wrote the paper.

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Correspondence to Dong-Hyuk Im.

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Jeon, M., Temuujin, O., Ahn, J. et al. Distributed L-diversity using spark-based algorithm for large resource description frameworks data. J Supercomput 77, 7270–7286 (2021). https://doi.org/10.1007/s11227-020-03583-6

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