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


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.


Anonymization Fingerprinting Collusion-resistance K-anonymity 

JEL classification

C88 - other computer software 


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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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