Skip to main content

Developed Framework Based on Cognitive Computing to Support Personal Data Protection Under the GDPR

  • Conference paper
  • First Online:
Modelling and Development of Intelligent Systems (MDIS 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1126))

Abstract

The General Data Protection Regulation (GDPR) has entered into force in the European Union (EU) since 25 May 2018 in order to satisfy present difficulties related to private information protection. This regulation involves significant structural for companies, but also stricter requirements for personal data collection, management, and protection. In this context, companies need to create smart solutions to allow them to comply with the GDPR and build a feeling of confidence in order to map all their personal data. In these conditions, cognitive computing could be able to assist companies extract, protect and anonymize sensitive structured and unstructured data. Therefore, this article proposes a framework that can serve as an approach or guidance for companies that use cognitive computing methods to meet GDPR requirements. The goal of this work is to examine the smart system as a data processing and data protection solution to contribute to GDPR compliance.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

References

  1. Storr, C., Storr, P.: Internet of things: right to data from a European perspective. In: Corrales, M., Fenwick, M., Forgó, N. (eds.) New Technology, Big Data and the Law. PLBI, pp. 65–96. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-5038-1_4

    Chapter  Google Scholar 

  2. Tikkinen-Piri, C., Rohunen, A., Markula, J.: EU general data protection regulation: changes and implications for personal data collecting companies. Comput. Law Secur. Rev. 34(1), 134–153 (2018)

    Article  Google Scholar 

  3. Voigt, P., von dem Bussche, A.: The EU General Data Protection Regulation (GDPR). Springer, Cham (2017). https://doi.org/10.1007/978-3-319-57959-7

    Book  Google Scholar 

  4. Becker, J., Knackstedt, R., Braeuer, S., Heddier, M.: Integrating regulatory requirements into information systems design and implementation. In: 35th International Conference on Information Systems “Building a Better World Through Information Systems”, ICIS 2014 (2014)

    Google Scholar 

  5. Sedkaoui, S., Gottinger, H-W.: The internet, data analytics and big data Chap. 8. In: Gottinger, H.W. (eds.) Internet Economics: Models, Mechanisms and Management, pp. 144–166. eBook Bentham Science Publishers, Sharjah (2017)

    Google Scholar 

  6. Mayer-Schonberger, V., Cukier, K.: Big Data: A Revolution That Will Transform How We Live, Work and Think. Houghton Mifflin Harcourt, Boston (2013)

    Google Scholar 

  7. Malatras, A., Aanchez, I., Beslay, L., et al.: Pan-European personal data breaches: mapping of current practices and recommendations to facilitate cooperation among data protection authorities. Comput. Law Secur. Rev. 33, 458–469 (2017)

    Article  Google Scholar 

  8. Tankard, C.: What the GDPR means for businesses. Netw. Secur. 6, 5–8 (2016)

    Article  Google Scholar 

  9. Auwermeulen, B.V.: How to attribute the right to data probability in the Europe: a comparative analysis of legislations. Comput. Law Secur. Rev. 33(1), 57–72 (2017)

    Article  Google Scholar 

  10. Data Protection Working Party, Article 29: Opinion 8/2014 on the on Recent Developments on the Internet of Things, WP 223, 16 September 2014

    Google Scholar 

  11. Mitrou, L.: Data Protection, Artificial Intelligence and Cognitive Services: Is the general data protection regulation (GDPR) “artificial intelligence-proof”? (2019). https://query.prod.cms.rt.microsoft.com/cms/api/am/binary/RE2PdYu

  12. Rizkallah, J.: The Big (Unstructured) Data Problem (2017). https://www.forbes.com/sites/forbestechcouncil/2017/06/05/the-big-unstructured-data-problem/#16ddb612493a

  13. Sedkaoui, S.: Data Analytics and Big Data. ISTE-Wiley, London (2018)

    Book  Google Scholar 

  14. General Data Protection Regulation (EU) (2016). http://data.consilium.europa.eu/doc/document/ST-5419-2016-INIT/en/pdf

  15. Robol, M., Salnitri, M., Giorgini, P.: Toward GDPR-compliant socio-technical systems: modeling language and reasoning framework. In: Poels, G., Gailly, F., Serral Asensio, E., Snoeck, M. (eds.) PoEM 2017. LNBIP, vol. 305, pp. 236–250. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70241-4_16

    Chapter  Google Scholar 

  16. Schwartz, P., Solove, D.: Reconciling personal information in the United States and European Union. Calif. Law Rev. 102, 877–916 (2014)

    Google Scholar 

  17. Zerlang, J.: GDPR: a milestone in convergence for cybersecurity and compliance. Netw. Secur. 6, 8–11 (2017)

    Article  Google Scholar 

  18. Earley, S.: Executive roundtable series: machine learning and cognitive computing. IT Prof. 17(4), 56–60 (2015)

    Article  Google Scholar 

  19. TechTarget: Cognitive Computing (2017). http://whatis.techtarget.com/definition/cognitive-computing

  20. Watson, H.: The cognitive decision-support generation. Bus. Intell. J. 22(2), 5–14 (2017)

    Google Scholar 

  21. Demirkan, H., Earley, S., Harmon, R.: Cognitive computing. IT professional 19(4), 16–20 (2017)

    Article  Google Scholar 

  22. Hurwitz, J., Kaufman, M., Bowles, A.: Cognitive Computing and Big Data Analytics. Wiley, Hoboken (2015)

    Google Scholar 

  23. Coccoli, M., Maresca, P.: Adopting cognitive computing solutions in healthcare. J. e-Learn. Knowl. Soc. 14(1) (2018)

    Google Scholar 

  24. Williams, H.: IBM pushes cognitive computing & data-driven solutions ahead of GDPR (2017). https://www.cbronline.com/internet-of-things/cognitive-computing/ibm-pushes-cognitive-computing-data-driven-solutions-ahead-gdpr/

  25. Gupta, S., Kumar, A.K., Baabdullah, A., Al-Khowaiter, W.A.A.: Big data with cognitive computing: a review for the future. Int. J. Inf. Manage. 42, 78–89 (2018)

    Article  Google Scholar 

  26. Alert Logic Report: GDPR Compliance in the EU (2017). https://www.alertlogic.com/assets/industry-reports/EU_GDPR_Alert_Logic.pdf

  27. Alert Logic Report: GDPR Compliance Report (2018). https://www.alertlogic.com/assets/industry-reports/2018_GDPR_Compliance_Report.pdf

  28. Hoepman, J.-H.: Privacy design strategies. In: Cuppens-Boulahia, N., Cuppens, F., Jajodia, S., Abou El Kalam, A., Sans, T. (eds.) SEC 2014. IAICT, vol. 428, pp. 446–459. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-55415-5_38

    Chapter  Google Scholar 

  29. Angelopoulos, K., Diamantopoulou, V., Mouratidis, H., Pavlidis, M.: A metamodel for GDPR-based privacy level agreements. In: ER Forum/Demos (2017)

    Google Scholar 

  30. Furey, E., Blue, J.: Alexa, emotions, privacy and GDPR. In: Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI 2018), Belfast, UK (2018)

    Google Scholar 

  31. Gan, M.F., Chua, H.N., Wong, S.F.: Personal data protection act enforcement with PETs adoption: an exploratory study on employees’ working process change. In: Kim, K.J., Kim, H., Baek, N. (eds.) ICITS 2017. LNEE, vol. 450, pp. 193–202. Springer, Singapore (2018). https://doi.org/10.1007/978-981-10-6454-8_25

    Chapter  Google Scholar 

  32. Karie, N.-M., Kebande, V.-R., Venter, H.S.: Diverging deep learning cognitive computing techniques into cyber forensics. Forensic Sci. Int. Synerg. 1, 61–67 (2019)

    Article  Google Scholar 

  33. DLA Piper Data Protection. https://www.dlapiperdataprotection.com/

  34. Falagas, M.E., Pitsouni, E.I., Malietzis, G.A., Pappas, G.: Comparison of PubMed, Scopus, web of science, and Google scholar: strengths and weaknesses. FASEB J. 22(2), 338–342 (2008). Official Publication of the Federation of American Societies for Experimental Biology

    Article  Google Scholar 

  35. EU Parliament: Home Page of EU GDPR (2017). https://www.eugdpr.org/

  36. Cormack, A.: GDPR: What’s your justification? (2017). https://community.jisc.ac.uk/blogs/regulatory-developments/article/gdpr-whats-your-justification

  37. Information Commissioner’s Office: Preparing for the General Data Protection Regulation (GDPR): 12 Steps to Take Now (2018). https://ico.org.uk/media/1624219/preparing-for-the-gdpr-12-steps.pdf

  38. Data Protection Network: GDPR Data Retention Quick Guide (2017). https://www.dpnetwork.org.uk/gdpr-data-retention-guide/

  39. Gantner, J., Demetz, L., Maier, R.: All you need is trust: an analysis of trust measures communicated by cloud providers. In: Debruyne, C., et al. (eds.) OTM 2015. LNCS, pp. 557–574. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-26148-5_38

    Chapter  Google Scholar 

  40. Sedkaoui, S., Khelfaoui, M.: Understand, develop and enhance the learning process with big data. Inf. Discov. Deliv. 47(1), 2–16 (2019)

    Google Scholar 

Download references

Acknowledgement

This research was realized under the “Eugen Ionescu” fellowship program, supported by “Agence Universitaire de Francophonie” (AUF) in Romania. The AUF team played no role in the writing of this article, or the decision to submit it for MDIS 2019 conference.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Soraya Sedkaoui .

Editor information

Editors and Affiliations

Ethics declarations

The authors declare no conflict of interest.

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sedkaoui, S., Simian, D. (2020). Developed Framework Based on Cognitive Computing to Support Personal Data Protection Under the GDPR. In: Simian, D., Stoica, L. (eds) Modelling and Development of Intelligent Systems. MDIS 2019. Communications in Computer and Information Science, vol 1126. Springer, Cham. https://doi.org/10.1007/978-3-030-39237-6_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-39237-6_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-39236-9

  • Online ISBN: 978-3-030-39237-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics