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On the role of contextual information for privacy attacks and classification
Název česky | O úloze konextových informací pro útoky proti a klasifikaci soukromí |
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Autoři | |
Rok publikování | 2004 |
Druh | Článek ve sborníku |
Konference | Proceedings of the 2004 IEEE International Conference on Data Mining, Workshop on Privacy and Security Aspects of Data Mining |
Fakulta / Pracoviště MU | |
Citace | |
Obor | Informatika |
Klíčová slova | Contextual Information; Privacy; Attacks; Classification |
Popis | Many papers and articles attempt to define or even quantify privacy, typically with a major focus on anonymity. A related research exercise in the area of evidence-based trust models for ubiquitous computing environments has given us an impulse to take a closer look at the definition(s) of privacy in the Common Criteria, which we then transcribed in a bit more formal manner. This lead us to a further review of unlinkability, and revision of another semi-formal model allowing for expression of anonymity and unlinkability -- the Freiburg Privacy Diamond. We propose new means of describing (obviously only observable) characteristics of a system to reflect the role of contexts for profiling -- and linking -- users with actions in a system. We believe this approach should allow for evaluating privacy in large data sets. |