Skip to main content
SpringerLink
Log in

Anonimisation, Impacts and Challenges into Big Data: A Case Studies

  • Conference paper
  • First Online:
Enterprise Information Systems (ICEIS 2020)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 417))

Included in the following conference series:

  • 1314 Accesses

Abstract

In a context in which privacy is increasingly demanded by citizens and by various institutions, reflected in protection laws, anonymity emerges as an essential tool. Both the General Data Protection Regulation (GDPR) in the EU and the Brazilian General Data Protection Law (LGPD) provide a softer regulation for anonymised data, compared to personal data. Despite the legal advantages in their use, anonymisation tools have limits that should be considered, especially when it comes to massive data contexts. The work seeks to analyze whether anonymisation techniques can satisfactorily ensure privacy in big data environments, without taking other measures in favor of privacy. Based on two hypothetical cases, we realized that the anonymisation techniques, although well implemented, must be associated with governance techniques to avoid latent breaches of privacy. Besides that, we point out some guidelines identified in the case studies for the use of anonymous data in Big Data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    The term is spelled with two variants: “anonymisation”, used in the European context; or “anonymization” used in the US context. We adopt in this article the European variant because the work uses the GDPR [19] as reference.

References

  1. Brasher, E.A.: Addressing the failure of anonymization: guidance from the European union’s general data protection regulation. Colum. Bus. L. Rev. p. 209 (2018)

    Google Scholar 

  2. Brkan, M.: Do algorithms rule the world? Algorithmic decision-making and data protection in the framework of the GDPR and beyond. Int. J. Law Inf. Technol. 27(2), 91–121 (2019)

    Article  Google Scholar 

  3. Carvalho, A.P., Canedo, E.D., Carvalho, F.P., Carvalho, P.H.P.: Anonymisation and compliance to protection data: Impacts and challenges into big data. In: 22th International Conference on Enterprise Information Systems, pp. 31–41 (2020)

    Google Scholar 

  4. Casanovas, P., De Koker, L., Mendelson, D., Watts, D.: Regulation of big data: perspectives on strategy, policy, law and privacy. Health Technol. 7(4), 335–349 (2017)

    Article  Google Scholar 

  5. Dalla Favera, R.B., da Silva, R.L.: Cibersegurança na união europeia e no mercosul: big data e surveillance versus privacidade e proteção de dados na internet. Revista de Direito, Governança e Novas Tecnologias 2(2), 112–134 (2016)

    Article  Google Scholar 

  6. De Mauro, A., Greco, M., Grimaldi, M.: A formal definition of big data based on its essential features. Lib. Rev. 65(3), 122–135 (2016)

    Google Scholar 

  7. Domingo-Ferrer, J.: Personal big data, GDPR and anonymization. In: Cuzzocrea, A., Greco, S., Larsen, H.L., Saccà, D., Andreasen, T., Christiansen, H. (eds.) FQAS 2019. LNCS (LNAI), vol. 11529, pp. 7–10. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-27629-4_2

    Chapter  Google Scholar 

  8. Fothergill, D.B., Knight, W., Stahl, B.C., Ulnicane, I.: Responsible data governance of neuroscience big data. Front. Neuroinf. 13, 28 (2019)

    Article  Google Scholar 

  9. Hintze, M., El Emam, K.: Comparing the benefits of pseudonymisation and anonymisation under the GDPR. J. Data Prot. Priv. 2(2), 145–158 (2018)

    Google Scholar 

  10. Jensen, M.H., Nielsen, P.A., Persson, J.S.: Managing big data analytics projects: the challenges of realizing value (2018)

    Google Scholar 

  11. Joyce, D.: Data associations and the protection of reputation online in Australia. Big Data Soc. 4(1), 2053951717709829 (2017)

    Article  Google Scholar 

  12. Koutli, M., et al.: Secure IoT e-health applications using vicinity framework and GDPR guidelines. In: 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS), pp. 263–270. IEEE (2019)

    Google Scholar 

  13. Lin, C., Wang, P., Song, H., Zhou, Y., Liu, Q., Wu, G.: A differential privacy protection scheme for sensitive big data in body sensor networks. Ann. Telecommun. 465–475 (2016). https://doi.org/10.1007/s12243-016-0498-7

  14. Liu, H.: Visions of big data and the risk of privacy protection: a case study from the Taiwan health databank project. Ann. Global Health 1(81), 77–78 (2015)

    Article  Google Scholar 

  15. Mehmood, A., Natgunanathan, I., Xiang, Y., Hua, G., Guo, S.: Protection of big data privacy. IEEE Access 4, 1821–1834 (2016)

    Article  Google Scholar 

  16. Mustafa, U., Pflugel, E., Philip, N.: A novel privacy framework for secure m-health applications: the case of the GDPR. In: 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3), pp. 1–9. IEEE (2019)

    Google Scholar 

  17. Pomares-Quimbaya, A., Sierra-Múnera, A., Mendoza-Mendoza, J., Malaver-Moreno, J., Carvajal, H., Moncayo, V.: Anonylitics: from a small data to a big data anonymization system for analytical projects. In: 21st International Conference on Enterprise Information Systems, pp. 61–71 (2019)

    Google Scholar 

  18. Popovich, C., Jeanson, F., Behan, B., Lefaivre, S., Shukla, A.: Big data, big responsibility! building best-practice privacy strategies into a large-scale neuroinformatics platform. Int. J. Popul. Data Sci. 1(1), 1–343 (2017)

    Google Scholar 

  19. Regulation, G.D.P.: EU data protection rules. European Commission, Accessed in October 9, 2019 (2018). https://ec.europa.eu/commission/priorities/justice-and-fundamental-rights/data-protection/2018-reform-eu-data-protection-rules_en

  20. da República, P.: Lei geral de acesso a informação (lai). Secretaria-Geral (2011). http://www.mpf.mp.br/atuacao-tematica/sci/normas-e-legislacao/legislacao/legislacao-em-ingles/law-12.527. Accessed 4 Feb 2020

  21. da República, P.: Lei geral de proteção de dados pessoais (LGPD). Secretaria-Geral (2018). https://www.pnm.adv.br/wp-content/uploads/2018/08/Brazilian-General-Data-Protection-Law.pdf. Accessed 19 Nov 2019

  22. Ryan, M., Brinkley, M.: Navigating privacy in a sea of change: new data protection regulations require thoughtful analysis and incorporation into the organization’s governance model. Int. Auditor 74(3), 61–63 (2017)

    Google Scholar 

  23. Shapiro, S.: Propositional, first-order and higher-order logics: basic definitions, rules of inference, examples. Natural Language Processing and Knowledge Representation: Language for Knowledge and Knowledge for Language. AAAI Press/The MIT Press, Menlo Park, CA (1995)

    Google Scholar 

  24. Ventura, M., Coeli, C.M.: Para além da privacidade: direito à informação na saúde, proteção de dados pessoais e governança. Cadernos de Saúde Pública 34, e00106818 (2018)

    Google Scholar 

  25. Zikopoulos, P., Eaton, C., et al.: Understanding big data: analytics for enterprise class hadoop and streaming data. McGraw-Hill Osborne Media (2011)

    Google Scholar 

Download references

Acknowledgments

This research work has the support of the Research SupportFoundation of the Federal District (FAPDF) research grant 05/2018.

Author information

Authors and Affiliations

  1. Electrical Engineering Department (ENE), University of Brasília (UnB), P.O. Box 4466, Brasília, DF, Brazil

    Artur Potiguara Carvalho, Edna Dias Canedo & Pedro Henrique Potiguara Carvalho

  2. Department of Computer Science, University of Brasília (UnB), P.O. Box 4466, Brasília, DF, Brazil

    Edna Dias Canedo

  3. Law School (FD), University of Brasília (UnB), Brasília, DF, Brazil

    Fernanda Potiguara Carvalho

Authors
  1. Artur Potiguara Carvalho
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Edna Dias Canedo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fernanda Potiguara Carvalho
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pedro Henrique Potiguara Carvalho
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Artur Potiguara Carvalho , Edna Dias Canedo or Fernanda Potiguara Carvalho .

Editor information

Editors and Affiliations

  1. Polytechnic Institute of Setúbal/INSTICC, Setúbal, Portugal

    Joaquim Filipe

  2. Warsaw University of Technology, Warsaw, Poland

    Michał Śmiałek

  3. George Mason University, Fairfax, VA, USA

    Alexander Brodsky

  4. MODESTE/ESEO, Angers, France

    Slimane Hammoudi

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Carvalho, A.P., Canedo, E.D., Carvalho, F.P., Carvalho, P.H.P. (2021). Anonimisation, Impacts and Challenges into Big Data: A Case Studies. In: Filipe, J., Śmiałek, M., Brodsky, A., Hammoudi, S. (eds) Enterprise Information Systems. ICEIS 2020. Lecture Notes in Business Information Processing, vol 417. Springer, Cham. https://doi.org/10.1007/978-3-030-75418-1_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-75418-1_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-75417-4

  • Online ISBN: 978-3-030-75418-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation