Securing Access to Complex Digital Artifacts – Towards a Controlled Processing Environment for Digital Research Data

  • Johann Latocha
  • Klaus Rechert
  • Isao Echizen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8092)

Abstract

Providing secured and restricted access to digital objects, especially access to digital research data, for a general audience poses new challenges to memory institutions. For instance, to protect individuals, only anonymized or pseudonymized data should be released to a general audience. Standard procedures have been established over time to cope with privacy issues of non-interactive digital objects like text, audio and video. Appearances of identifiers and potentially also quasi-identifiers were removed by a simple overlay, e.g. in text documents such appearances were simply blackened out. Today’s digital artifacts, especially research data, have complex, non-linear and even interactive manifestations. Thus, a different approach to securing access to complex digital artifacts is required. This paper presents an architecture and technical methods to control access to digital research data.

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References

  1. 1.
    Carlisle, D.M., Rodrian, M.L., Diamond, C.L.: California inpatient data reporting manual, medical information reporting for california (5th ed). Tech. rep., Office of Statewide Health Planning and Development (2007)Google Scholar
  2. 2.
    Kifer, D., Gehrke, J.: Injecting utility into anonymized datasets. In: Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, SIGMOD 2006, pp. 217–228. ACM, New York (2006)CrossRefGoogle Scholar
  3. 3.
    Li, T., Li, N.: On the tradeoff between privacy and utility in data publishing. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2009, pp. 517–526. ACM, New York (2009)CrossRefGoogle Scholar
  4. 4.
    Fung, B.C.M., Wang, K., Chen, R., Yu, P.S.: Privacy-preserving data publishing: A survey of recent developments. ACM Comput. Surv. 42(4), 14:1–14:53 (2010)Google Scholar
  5. 5.
    Wohlgemuth, S., Echizen, I., Sonehara, N., Müller, G.: Tagging disclosures of personal data to third parties to preserve privacy. In: Rannenberg, K., Varadharajan, V., Weber, C. (eds.) Security and Privacy – Silver Linings in the Cloud. IFIP AICT, vol. 330, pp. 241–252. Springer, Heidelberg (2010)Google Scholar
  6. 6.
    Rechert, K., Valizada, I., von Suchodoletz, D., Latocha, J.: bwFLA – a functional approach to digital preservation. PIK – Praxis der Informationsverarbeitung und Kommunikation 35(4), 259–267 (2012)Google Scholar
  7. 7.
    von Suchodoletz, D., Rechert, K., Welte, R., van den Dobbelsteen, M., Roberts, B., van der Hoeven, J., Schroder, J.: Automation of flexible migration workflows. International Journal of Digital Curation 2(2) (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Johann Latocha
    • 1
  • Klaus Rechert
    • 1
  • Isao Echizen
    • 2
  1. 1.University of FreiburgFreiburgGermany
  2. 2.National Institute of InformaticsChiyoda-kuJapan

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