Open AccessDoes additional information always reduce anonymity?
Author(s) -
Claudia Díaz,
Carmela Troncoso,
George Danezis
Publication year - 2007
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/1314333.1314347
Subject(s) - anonymity , conditional entropy , entropy (arrow of time) , computer science , a priori and a posteriori , information diagram , information theory , data mining , principle of maximum entropy , mathematics , statistics , artificial intelligence , binary entropy function , computer security , maximum entropy thermodynamics , physics , philosophy , epistemology , quantum mechanics
We discuss information-theoretic anonymity metrics, that use entropy over the distribution of all possible recipients to quantify anonymity. We identify a common misconception: the entropy of the distribution describing the potentialreceivers does not always decrease given more information.We show the relation of these a-posteriori distributions with the Shannon conditional entropy, which is an average overall possible observations.
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