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International Conference on Conceptual Modeling

ER 2018: Conceptual Modeling pp 497–504Cite as

How the Conceptual Modelling Improves the Security on Document Databases

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11157))

Abstract

Big Data is becoming a prominent trend in our society. Ever larger amounts of data, including sensitive and personal information, are being loaded into NoSQL and other Big Data technologies for analysis and processing. However, current security approaches do not take into account the special characteristics of these technologies, leaving sensitive and personal data unprotected, thereby risking severe monetary losses and brand damage. In this paper, we focus on assuring document databases, proposing a framework that considers three stages: (1) The source data set is analysed by using Natural Language Processing techniques and ontological resources, in order to detect sensitive data. (2) We define a metamodel for document databases that allows designers to specify both structural and security aspects. (3) This model is automatically implemented into a specific document database tool, MongoDB. Finally, we apply the proposed framework to a case study with a data set from the medical domain. The great advantages of our framework are that: (1) the effort required to secure the data is reduced, as part of the process is automated, (2) it can be easily applied to other NoSQL technologies by adapting the metamodel and transformations, and (3) it is aligned with existing standards, thus facilitating the application of recommendations and best practices.

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Notes

  1. 1.

    https://github.com/GSYAtools.

  2. 2.

    http://wordnetweb.princeton.edu/perl/webwn (visited on April, 2018).

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Acknowledgments

This work has been developed within the SEQUOIA Project, funded by Fondo Europeo de Desarrollo Regional FEDER and Ministerio de Economía y Competitividad, (TIN2015-63502-C3-1-R) (MINECO/FEDER).

Author information

Authors and Affiliations

  1. ISTR Research Group, Department of Computer Science and Electronics, University of Cantabria, Santander, Spain

    Carlos Blanco & Diego García-Saiz

  2. LUCENTIA Research Group, Languages and Computing Systems Department, University of Alicante, Alicante, Spain

    Jesús Peral, Alejandro Maté & Alejandro Oliver

  3. GSyA Research Group, Institute of Information Technologies and Systems, Information Systems and Technologies Department, University of Castilla-La Mancha, Toledo, Spain

    Carlos Blanco & Eduardo Fernández-Medina

Authors
  1. Carlos Blanco
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  2. Diego García-Saiz
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  3. Jesús Peral
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  4. Alejandro Maté
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  5. Alejandro Oliver
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  6. Eduardo Fernández-Medina
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Corresponding author

Correspondence to Carlos Blanco .

Editor information

Editors and Affiliations

  1. Lucentia, University of Alicante, Alicante, Spain

    Juan C. Trujillo

  2. Miami University, Oxford, OH, USA

    Karen C. Davis

  3. Renmin University of China, Beijing, China

    Xiaoyong Du

  4. Northwestern Polytechnical University, Xian, China

    Zhanhuai Li

  5. Department of Computer Science, National University of Singapore, Singapore, Singapore

    Tok Wang Ling

  6. Department of Computer Science and Technology, Tsinghua University, Beijing, Beijing, China

    Guoliang Li

  7. National University of Singapore, Singapore, Singapore

    Mong Li Lee

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Blanco, C., García-Saiz, D., Peral, J., Maté, A., Oliver, A., Fernández-Medina, E. (2018). How the Conceptual Modelling Improves the Security on Document Databases. In: Trujillo, J., et al. Conceptual Modeling. ER 2018. Lecture Notes in Computer Science(), vol 11157. Springer, Cham. https://doi.org/10.1007/978-3-030-00847-5_36

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  • DOI: https://doi.org/10.1007/978-3-030-00847-5_36

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00846-8

  • Online ISBN: 978-3-030-00847-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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