Differential Privacy versus Quantitative Information Flow

Differential privacy is a notion of privacy that has become very popular in the database community. Roughly, the idea is that a randomized query mechanism provides sufficient privacy protection if the ratio between the probabilities of two different entries to originate a certain answer is bound by e . In the fields of anonymity and information flow there is a similar concern for controlling information leakage, i.e. limiting the possibility of inferring the secret information from the observables. In recent years, researchers have proposed to quantify the leakage in terms of the information-theoretic notion of mutual information. There are two main approaches that fall in this category: One based on Shannon entropy, and one based on R

• Type: Journal
• Year: 2010
• Where: CORR
• Authors: Mário S. Alvim, Konstantinos Chatzikokolakis, Pierpaolo Degano, Catuscia Palamidessi
• Keywords: CORR 2010, Education, Mutual Information, Randomized Query Mechanism, Sufficient Privacy Protection