Section: New Results

Minimum Exposure

Participants : Nicolas Anciaux, Marouane Fazouane, Benjamin Nguyen [correspondent] , Michalis Vazirgiannis.

When users request a service, the service provider usually asks for personal documents to tailor its service to the specific situation of the applicant. For example, the rate and duration of consumer’s loans are usually adapted depending on the risk based on the income, assets or past lines of credits of the borrower. In practice, an excessive amount of personal data is collected and stored. Indeed, a paradox is at the root of this problem: service providers require users to expose data in order to determine whether that data is needed or not to achieve the purpose of the service. We explore a reverse approach, where service providers would publicly describe the data they require to complete their task, and where software (placed, depending on the context, on the client, on the server, or in a trusted hardware component) would use those descriptions to determine a minimum subset of information to expose.

Following our 2012 seminal works on the general Minimum Exposure framework, we have pursued its general study in 2013 [15] , [29] . We have also developed a prototype system, using a low powered and highly secure smartcard [21] , which is used to support hidden decision rules.