2012 | OriginalPaper | Buchkapitel
An Algorithm for k-Anonymity-Based Fingerprinting
verfasst von : Sebastian Schrittwieser, Peter Kieseberg, Isao Echizen, Sven Wohlgemuth, Noboru Sonehara, Edgar Weippl
Erschienen in: Digital Forensics and Watermarking
Verlag: Springer Berlin Heidelberg
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The anonymization of sensitive microdata (e.g. medical health records) is a widely-studied topic in the research community. A still unsolved problem is the limited informative value of anonymized microdata that often rules out further processing (e.g. statistical analysis). Thus, a tradeoff between anonymity and data precision has to be made, resulting in the release of partially anonymized microdata sets that still can contain sensitive information and have to be protected against unrestricted disclosure. Anonymization is often driven by the concept of
k
-anonymity that allows fine-grained control of the anonymization level. In this paper, we present an algorithm for creating unique fingerprints of microdata sets that were partially anonymized with
k
-anonymity techniques. We show that it is possible to create different versions of partially anonymized microdata sets that share very similar levels of anonymity and data precision, but still can be uniquely identified by a robust fingerprint that is based on the anonymization process.