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International Conference on Modeling Decisions for Artificial Intelligence

MDAI 2017: Modeling Decisions for Artificial Intelligence pp 3–11Cite as

Provenance and Privacy

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10571)

Abstract

This paper presents an overview of current needs on data provenance and data privacy, and discusses state-of-the-art results in this area. The paper highlights the difficulties that we need to face and finishes with some lines that require further work.

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  • DOI: 10.1007/978-3-319-67422-3_1
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Notes

  1. 1.

    Regulation (EU) 2016/679 of the European Parliament and of the Council: http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32016R0679.

References

  1. Ahlborg, K.: Vem har skrivit det falska brevet om Sverige? Aftonbadet 12th September 2015. http://www.aftonbladet.se/nyheter/article21407033.ab

  2. Akoush, S., Sohan, R., Hopper, A.: HadoopProv: towards Provenance as a first class citizen in MapReduce. In: Presented as Part of the 5th USENIX Workshop on the Theory and Practice of Provenance (2013)

    Google Scholar 

  3. Arab, B., Gawlick, D., Radhakrishnan, V., Guo, H., Glavic, B.: A generic provenance middleware for queries, updates, and transactions. In: 6th USENIX Workshop on the Theory and Practice of Provenance (2014)

    Google Scholar 

  4. Braun, U., Shinnar, A., Seltzer, M.: Securing provenance. In: Proceedings of the HOTSEC (2008)

    Google Scholar 

  5. Ciccarese, P., Wu, E., Wong, G., Ocana, M., Kinoshita, J., Ruttenberg, A., Clark, T.: The SWAN biomedical discourse ontology. J. Biomed. Inform., Semant. Mashup Biomed. Data 41, 739–751 (2008). doi:10.1016/j.jbi.2008.04.010

  6. Domingo-Ferrer, J., Torra, V.: A quantitative comparison of disclosure control methods for microdata. In: Doyle, P., Lane, J.I., Theeuwes, J.J.M., Zayatz, L. (eds.) Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies, North-Holland, pp. 111–134 (2001)

    Google Scholar 

  7. Dwork, C.: Differential privacy. In: Bugliesi, M., Preneel, B., Sassone, V., Wegener, I. (eds.) ICALP 2006. LNCS, vol. 4052, pp. 1–12. Springer, Heidelberg (2006). doi:10.1007/11787006_1

    CrossRef  Google Scholar 

  8. Gil, Y., Miles, S. (eds.): PROV Model Primer (2013)

    Google Scholar 

  9. Google.: European privacy requests for search removals (2016). https://www.google.com/transparencyreport/removals/europeprivacy/?hl=en

  10. Hartig, O., Zhao, J.: Publishing and consuming provenance metadata on the web of linked data. In: McGuinness, D.L., Michaelis, J.R., Moreau, L. (eds.) IPAW 2010. LNCS, vol. 6378, pp. 78–90. Springer, Heidelberg (2010). doi:10.1007/978-3-642-17819-1_10

    CrossRef  Google Scholar 

  11. Hasan, R., Sion, R., Winslett, M.: Introducing secure provenance: problems and challenges. In: Proceedings of the StorageSST. ACM (2007)

    Google Scholar 

  12. Hasan, R., Sion, R., Winslett, M.: The case of the fake Picasso: preventing history forgery with secure provenance. In: Proceedings of the FAST (2009)

    Google Scholar 

  13. HL7 Standards Product Brief - HL7 CDA? R2 Implementation Guide: Data Provenance, Release 1 - US Realm [WWW Document], n.d. http://www.hl7.org/implement/standards/product_brief.cfm?product_id=420. Accessed 04 Apr 2016

  14. Interlandi, M., Shah, K., Tetali, S.D., Gulzar, M.A., Yoo, S., Kim, M., Millstein, T., Condie, T.: Titian: data provenance support in Spark. Proc. VLDB Endow 9, 216–227 (2015)

    Google Scholar 

  15. Logothetis, D., De, S., Yocum, K.: Scalable Lineage Capture for Debugging DISC Analytics, pp. 1–15. ACM Press, New York (2013). doi:10.1145/2523616.2523619

  16. McDaniel, P., Butler, K., Sion, R., Zadok, E., Winslett, M.: Towards a secure and efficient system for end-to-end provenance. In: Proceedings of the TAPP (2010)

    Google Scholar 

  17. Moreau, L., Freire, J., Futrelle, J., McGrath, R.E., Myers, J., Paulson, P.: The open provenance model: an overview. In: Freire, J., Koop, D., Moreau, L. (eds.) IPAW 2008. LNCS, vol. 5272, pp. 323–326. Springer, Heidelberg (2008). doi:10.1007/978-3-540-89965-5_31

    CrossRef  Google Scholar 

  18. Niu, X., Glavic, B., Gawlick, D., Liu, Z.H., Krishnaswamy, V., Radhakrishnan, V.: Interoperability for Provenance-aware Databases using PROV and JSON. In: 7th USENIX Workshop on the Theory and Practice of Provenance (2015)

    Google Scholar 

  19. Oracle Enterprise Metadata Management Overview [WWW Document], n.d. http://www.oracle.com/technetwork/middleware/oemm/overview/index.html. Accessed 04 Apr 2016

  20. Park, H., Ikeda, R., Widom, J.: RAMP: a system for capturing and tracing provenance in MapReduce workflows. In: Presented at the 37th International Conference on Very Large Data Bases, Stanford InfoLab, Seattle, Washington (2011)

    Google Scholar 

  21. Pearson, S., Mont, M.C.: Sticky Policies: An approach for managing privacy across multiple parties, Computer, pp. 60–68 (2011)

    Google Scholar 

  22. PCAST.: Big data and privacy: a technological perspective, President’s Council of Advisors on Science and Technology, Executive office of the president of the United States (2014)

    Google Scholar 

  23. Sahoo, S.S., Sheth, A.P.: Provenir ontology: towards a framework for eScience provenance management. Microsoft eScience Workshop (2009)

    Google Scholar 

  24. Samarati, P.: Protecting Respondents’ Identities in Microdata Release. IEEE Trans. Knowl. Data Eng. 13(6), pp. 1010–1027 (2001)

    Google Scholar 

  25. Thurfjell, K.: Sverige erbjuder sig sälja vapen till Ukraina i förfalskat brev, Svenska Dagbladet (2015). http://www.svd.se/sverige-erbjuder-sig-salja-vapen-till-ukraina-i-forfalskat-brev

  26. Torra, V., Navarro-Arribas, G.: Data Privacy. WIREs Data Min. Knowl. Discov. 4(4), pp. 269–280 (2014)

    Google Scholar 

  27. http://wiki.siframework.org/Data+Provenance+Initiative

  28. Winkler, W.E.: Re-identification methods for masked microdata. In: Domingo-Ferrer, J., Torra, V. (eds.) PSD 2004. LNCS, vol. 3050, pp. 216–230. Springer, Heidelberg (2004). doi:10.1007/978-3-540-25955-8_17

    CrossRef  Google Scholar 

  29. Zhang, J., Chapman, A., LeFevre, K.: Do you know where your data’s been? – tamper-evident database provenance. In: Jonker, W., Petković, M. (eds.) SDM 2009. LNCS, vol. 5776, pp. 17–32. Springer, Heidelberg (2009). doi:10.1007/978-3-642-04219-5_2

    CrossRef  Google Scholar 

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Acknowledgements

Partially supported by Vetenskapsrådet project: “Disclosure risk and transparency in big data privacy” (VR 2016-03346); and Spanish and Catalan governments with projects TIN2014-55243-P and 2014SGR-691 respectively.

Author information

Authors and Affiliations

  1. School of Informatics, University of Skövde, Skövde, Sweden

    Vicenç Torra

  2. Department of Information and Communication Engineering, Universitat Autònoma de Barcelona, Barcelona, Spain

    Guillermo Navarro-Arribas

  3. CA Technologies, Barcelona, Spain

    David Sanchez-Charles & Victor Muntés-Mulero

Authors
  1. Vicenç Torra
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  2. Guillermo Navarro-Arribas
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  3. David Sanchez-Charles
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  4. Victor Muntés-Mulero
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Corresponding author

Correspondence to Guillermo Navarro-Arribas .

Editor information

Editors and Affiliations

  1. University of Skövde, Skövde, Sweden

    Vicenç Torra

  2. Toho Gakuen, Kunitachi, Tokyo, Japan

    Yasuo Narukawa

  3. Kyushu Institute of Technology, Iizuka, Fukuoka, Japan

    Aoi Honda

  4. Kyushu Institute of Technology, Kitakyushu-shi, Fukuoka, Japan

    Sozo Inoue

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Torra, V., Navarro-Arribas, G., Sanchez-Charles, D., Muntés-Mulero, V. (2017). Provenance and Privacy. In: Torra, V., Narukawa, Y., Honda, A., Inoue, S. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2017. Lecture Notes in Computer Science(), vol 10571. Springer, Cham. https://doi.org/10.1007/978-3-319-67422-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-67422-3_1

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