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Electronic Markets

, Volume 24, Issue 2, pp 113–124 | Cite as

An algorithm for collusion-resistant anonymization and fingerprinting of sensitive microdata

  • Peter Kieseberg
  • Sebastian Schrittwieser
  • Martin Mulazzani
  • Isao Echizen
  • Edgar Weippl
Special Theme

Abstract

The collection, processing, and selling of personal data is an integral part of today’s electronic markets, either as means for operating business, or as an asset itself. However, the exchange of sensitive information between companies is limited by two major issues: Firstly, regulatory compliance with laws such as SOX requires anonymization of personal data prior to transmission to other parties. Secondly, transmission always implicates some loss of control over the data since further dissemination is possible without knowledge of the owner. In this paper, we extend an approach based on the utilization of k-anonymity that aims at solving both concerns in one single step - anonymization and fingerprinting of microdata such as database records. Furthermore, we develop criteria to achieve detectability of colluding attackers, as well as an anonymization strategy that resists combined efforts of colluding attackers on reducing the anonymization-level. Based on these results we propose an algorithm for the generation of collusion-resistant fingerprints for microdata.

Keywords

Anonymization Fingerprinting Collusion-resistance K-anonymity 

JEL classification

C88 - other computer software 

References

  1. Al-Haj, A., & Odeh, A. (2008). Robust and blind watermarking of relational database systems. Journal of Computer Science, 4(12), 1024–1029.CrossRefGoogle Scholar
  2. Celik, M., Sharma, G., & Tekalp, A. (2003). Collusion-resilient fingerprinting using random prewarping. Proceedings of the International Conference on Image processing, ICIP 2003. vol. 1, pp. 1–509, IEEE.Google Scholar
  3. Dalenius, T. (1986). Finding a needle in a haystack – or identifying anonymous census record. Journal of Official Statistics, 2(3), 329–336.Google Scholar
  4. Dittmann, J., Schmitt, P., Saar, E., Ueberberg, J., & Schwenk, J. (2000). Combining digital watermarks and collusion secure fingerprints for digital images. Journal of Electronic Imaging, 9(4), 456–467.CrossRefGoogle Scholar
  5. El Emam, K., Dankar, F., Issa, R., Jonker, E., Amyot, D., Cogo, E., et al. (2009). A globally optimal k-anonymity method for the de-identification of health data. Journal of the American Medical Informatics Association, 16(5), 670–682.CrossRefGoogle Scholar
  6. Fotopoulos, V., & Skodras, A. (2003). Digital image watermarking: an overview. EURASIP Newsletter, 14(4).Google Scholar
  7. Gross-Amblard, D. (2003). Query-preserving watermarking of relational databases and xml documents. SIGART Symposium on Principles of Database Systems.Google Scholar
  8. Hartung, F., & Kutter, M. (1999). Multimedia watermarking techniques. Proceedings of the IEEE, 87(7), 1079–1107.CrossRefGoogle Scholar
  9. Lafaye, J. (2007). An analysis of database watermarking security. Symposium on Information assurance and security.Google Scholar
  10. Langelaar, G., Setyawan, I., & Lagendijk, R. (2000). Watermarking digital image and video data. A state-of-the-art overview. IEEE Signal Processing Magazine, 17(5), 20–46.CrossRefGoogle Scholar
  11. Li, W., Yuan, Y., Li, X., Xue, X., & Lu, P. (2005). Overview of digital audio watermarking. Tongxin Xuebao (Journal on Communications), 26(2), 100–111.Google Scholar
  12. Liu, S., Wang, S., Deng, R., & Shao, W. (2005). A block oriented fingerprinting scheme in relational database. Information Security and Cryptologyy–ICISC 2004 (pp. 455-466). Berlin Heidelberg: Springer.Google Scholar
  13. Machanavajjhala, A., Kifer, D., Gehrke, J., & Venkitasubramaniam, M. (2007). l-diversity: privacy beyond k-anonymity. ACM Transactions on Knowledge Discovery from Data, 1, 3.CrossRefGoogle Scholar
  14. Samarati, P. (2001). Protecting respondents’ identities in microdata release. IEEE Transactions on Knowledge and Data Engineering, 13, 1010–1027.CrossRefGoogle Scholar
  15. Schrittwieser S., Kieseberg P., Echizen I., Wohlgemuth S., & Sonehara N. (2011a). Using generalization patterns for fingerprinting sets of partially anonymized microdata in the course of disasters, RISI 2011.Google Scholar
  16. Schrittwieser S., Kieseberg P., Echizen I., Wohlgemuth S., Sonehara N., & Weippl E. (2011b). An Algorithm for k-anonymity-based Fingerprinting, IWDW 2011.Google Scholar
  17. Seo, J., Jin, M., Lee, S., Jang, D., Lee, S., & Yoo, C. (2005). Audio fingerprinting based on normalized spectral subband centroids. International Conference on Acoustics, Speech, and Signal Processing, 3, 213–216.Google Scholar
  18. Sion, R., Atallah, M., & Prabhakar, S. (2002). Watermarking relational databases.Google Scholar
  19. Su, K., Kundur, D., & Hatzinakos, D. (2002). A novel approach to collusion-resistant video watermarking. Proceedings of SPIE (4675).Google Scholar
  20. Su, K., Kundur, D., & Hatzinakos, D. (2005). Statistical invisibility for collusion-resistant digital video watermarking. IEEE Transactions on Multimedia, 7(1), 43–51.CrossRefGoogle Scholar
  21. Sweeney, L. (2002a). Achieving k-anonymity privacy protection using generalization and suppression. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 10(5), 571–588.CrossRefGoogle Scholar
  22. Sweeney, L. (2002b). Comments to the Department of Health and Human Services On "Standards of Privacy of Individually Identifiable Health Information.Google Scholar
  23. Sweeney, L., et al. (2002). k-anonymity: a model for protecting privacy. International Journal of Uncertainty Fuzziness and Knowledge Based Systems, 10(5), 557–570.CrossRefGoogle Scholar
  24. Trappe, W., Wu, M., Wang, Z., & Liu, K. (2003). Anti-collusion fingerprinting for multimedia. IEEE Transactions on Signal Processing, 51(4), 1069–1087.CrossRefGoogle Scholar
  25. Willenborg, L., & De Waal, T. (1996). Statistical disclosure control in practice. New York: Springer Verlag.CrossRefGoogle Scholar
  26. Willenborg, L., & Kardaun, J. (1999). Fingerprints in microdata sets. Joint ECE/Eurostat Work Session on Statistical Data Confidentiality.Google Scholar
  27. Wu, M., Trappe, W., Wang, Z., & Liu, K. (2004). Collusion-resistant fingerprinting for multimedia. IEEE Signal Processing Magazine, 21(2), 28–39.CrossRefGoogle Scholar
  28. Zhang, Z., Jin, X., Wang, J., & Li, D. (2004). Watermarking relational database using image. International Conference on Machine Learning and Cybernetics, 3, 1739–1744.Google Scholar

Copyright information

© Institute of Information Management, University of St. Gallen 2014

Authors and Affiliations

  • Peter Kieseberg
    • 1
  • Sebastian Schrittwieser
    • 2
  • Martin Mulazzani
    • 1
  • Isao Echizen
    • 3
  • Edgar Weippl
    • 1
  1. 1.SBA Research gGmbHViennaAustria
  2. 2.St. Pölten University of Applied SciencesPöltenAustria
  3. 3.National Institute of InformaticsTokyo Japan

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