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Privacy-preserving data mining, sharing and publishing

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The goal of the paper is to present different approaches to privacy-preserving data sharing and publishing in the context of e-health care systems. In particular, the literature review on technical issues in privacy assurance and current real-life high complexity implementation of medical system that assumes proper data sharing mechanisms are presented in the paper.
Rocznik
Tom
Strony
69--76
Opis fizyczny
Bibliogr. 29 poz., rys.
Twórcy
autor
  • Wroclaw University of Technology, Wroclaw, Poland
autor
Bibliografia
  • [1] Department of Health and Human Services, Standards for Privacy of Individually Identifiable Health Information, Final Rule, Federal Register, Vol. 67, No. 157, 2002.
  • [2] HENNESSY S., LAUER G., ZUNIC N., GERBER B., NELSON A., Data-centric security: Integrating data privacy and data security, IBM Journal of Research and Development, Vol. 53, No. 2, 2009, pp. 1-12.
  • [3] BERTINO E., BRODIE C., CALO S. B., CRANOR L.F., KARAT C., KARAT J., LI N., LIN D., LOBO J., NI Q., RAO P.R., WANG X., Analysis of privacy and security policies, IBM Journal of Research and Development, Vol. 53, No. 2, 2009, pp. 1-18.
  • [4] EVFIMIEVSKI A., GRANDISON T., Privacy-Preserving Data Mining, In: FERRAGGINE V.E., DOORN J.H., RIVERO L.C. (eds.), Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends, 2009, pp. 527-536.
  • [5] LOUKIDES, G., SHAO J., Preventing range disclosure in k-anonymised data, Expert Systems with Applications, Vol. 38, No. 4, 2011, pp. 4559-4574.
  • [6] SAMARATI P., SWEENEY L., Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression, Proceedings of the IEEE Symposium on Research in Security and Privacy, Oakland, CA, 1998.
  • [7] WARNER S. L., Randomized response: A survey technique for eliminating evasive answer bias, Journal of the American Statistical Association, Vol. 60, No. 309, 1965, pp. 63-69.
  • [8] AGRAWAL R., SRIKANT R., Privacy preserving data mining, Proceedings of ACM SIGMOD Conference on Management of Data (SIGMOD’00), Dallas, TX, 2000.
  • [9] LINDELL Y., PINKAS B., Privacy preserving data mining, Lecture Notes in Computer Science, LNCS 1880, Proceedings of Advances in Cryptology: Crypto’00, Springer, 2000, pp. 20-24.
  • [10] FUNG B., WANG K., CHEN R., YU P., Privacy-preserving data publishing: a survey on recent developments, ACM Computing Surveys, Vol. 42, No. 4, 2010, article no. 14, pp. 1-53.
  • [11] GOLDREICH O., Foundations of cryptography, Cambridge University Press, 2004.
  • [12] STINSON D. R., Cryptography theory and practice, Chapman & Hall/CRC, 2006.
  • [13] LI X., MOTIWALLA L., Protecting Patient Privacy With Data Masking, Association of Information Systems SIGSEC Workshop on Information Security & Privacy, Phoenix, USA, 2009, pp. 7-11.
  • [14] DEFAYS D., NANOPOULOS P., Panels of Enterprises and Confidentiality: The Small Aggregates Method, Proceedings of Statistics Canada, Symposium 92 on Design and Analysis of Longitudinal Surveys, Ottawa, Canada, 1992, pp. 195-204.
  • [15] DOMINGO-FERRER J., MATEO-SANZ J., Practical Data-Oriented Microaggregation for Statistical Disclosure Control, IEEE Transactions on Knowledge and Data Engineering, Vol. 14, No. 1, 2002, pp. 189-201.
  • [16] My HealtheVet - The Gateway to Veteran Health and Wellness, http://www.myhealth.va.gov/, 2007.
  • [17] TRAUB J., YEMINI Y., WOZNIAKOWSKI H., The Statistical Security of a Statistical Database, ACM Transactions on Database Systems, Vol. 4, No. 9, 1984, pp. 672-679.
  • [18] ADAM N., WORTMANN J., Security-Control Methods for Statistical Databases: A Comparative study, ACM Computing Surveys, Vol. 21, No. 4, 1989, pp. 515 –556.
  • [19] SWEENEY L., k-Anonymity: A Model for Protecting Privacy, International Journal on Uncertainty, Fuzziness and Knowledge-based Systems, Vol. 10, No. 5, 2002, pp. 557-570.
  • [20] LI X., SARKAR S., Privacy Protection in Data Mining: A Perturbation Approach for Categorical Data, Information Systems Research, Vol. 17, No. 3, 2006, pp. 254-270.
  • [21] GARDNER J., XIONG L., An integrated framework for de-identifying unstructured medical data, Data & Knowledge Engineering, Vol. 68, Issue 12, 2009.
  • [22] TROJER T., LEE C.K., FUNG B., NARUPIYAKUL L., HUNG P., Privacy-Aware Health Information Sharing, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques, Data Mining and Knowledge Discovery Series, Chapman & Hall/CRC, 2010.
  • [23] EMAM K. E., Data anonymization practices in clinical research: A descriptive study, Tech. rep., Access to Information and Privacy Division of Health, Canada, 2006.
  • [24] GKOULALAS-DIVANIS A., SAYGIN Y., PEDRESCHI D., Privacy in Mobility Data Mining, SIGKDD Explorations, Vol. 13, No. 1, 2002, pp. 4-5.
  • [25] NICHOLSON L., The Internet and Healthcare, Chicago, Health Administration Press, 1999.
  • [26] KURTZ G., Confidentiality and Information Security, Journal of Healthcare Information Management, Vol. 17, No. 3, 2001, pp. 41-48.
  • [27] SWEENEY L., Guaranteeing anonymity when sharing medical data, the Datafly system, In Proceedings of AMIA Annual Fall Symposium, American Medical Informatics Association, 1997, pp. 51-55.
  • [28] MICHALSKI M., KOŹBA W., NIECZKOWSKI T., RYFA L., Identification, analysis and classification of medical records as well as models for their acquisition and sharing for treatment purposes and health care policy taking into account syntactic, semantic and quantitative data features at the national and international level (Identyfikacja, analiza i klasyfikacja typów danych medycznych oraz określenie modeli ich gromadzenia i udostępniania na potrzeby leczenia oraz prowadzenia polityki ochrony zdrowia z uwzględnieniem aspektów syntaktycznych i semantycznych oraz ilościowych tych danych w kontekście doświadczeń krajowych i międzynarodowych), Sygnity, 2010, (in polish).
  • [29] Electronic Platform for Collection, Analysis and Sharing of Digital Medical Records (Elektroniczna Platforma Gromadzenia, Analizy i Udostępniania Zasobów Cyfrowych o Zdarzeniach Medycznych), Ernst & Young, 2009, (in polish).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0025-0007
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