Section: New Results

Secure Global Computing on Asymmetric Architecture

Participants : Tristan Allard, Benjamin Nguyen, Philippe Pucheral, Quoc-Cuong To.

This research direction is based on the asymmetric architecture, composed of a powerful, available and untrusted computing infrastructure (server or cloud), and a large set of low powered, highly disconnected trusted devices. Trust is assumed ad hoc and can be justified by the use of secure tokens, open source software, friend relationships etc. In our work, we use tamper resistant secure tokens running trusted software, which provide a high degree of trust, due to the overwhelming cost of hardware tampering. The main difficulty on such an architecture is global processing i.e. constructing aggregate data from the individual records, because the entity in charge of executing the global computation is untrusted. Given our large scale data centric applications (e.g. nationwide surveys), we also discard solutions based on secure multi-party computation, which do not scale. We have studied the execution of Privacy Preserving Data Publishing (PPDP) algorithms on such an architecture, and provided generic protocols to deal with all kinds of PPDP algorithms, which are robust against honest-but-curious and malicious adversaries. This work is an extension of [31] We are now studying more generally the execution of SQL "Group by" queries on this architecture, which is the topic of Quoc-Cuong To's Ph.D. thesis started in sept. 2012. We have published preliminary results on this novel problem in [23] , which adapts the techniques proposed in [31] .