Description
Access to encrypted data is often “all-or-nothing” : either one has to decrypt everything, or one cannot read anything. Following Gentry’s work in 2009, fully homomorphic encryption has gained more and more attention, in particular because it allows more flexibility on encrypted data access and process. It is now possible to evaluate functions on encrypted data and get only the result – encrypted as well. This possibility offers numerous applications, especially when building a trustworthy cloud provider where the server cannot access the users’ data. It theoretically reconciles a rich user experience with protection of her sensible data. However, efficiency of fully homomorphic encryption remains seriously undermined by a very costly procedure: the “bootstrapping”. In this talk, we will show how to use graph problems and integer linear programming in order to determine the minimal number of bootstrappings necessary to correctly evaluate a circuit over encrypted data. Our method allows significant efficiency gains in the evaluation process, saving up to 70% bootstrappings calls. This is a joint work with Bastien Vialla.
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Symmetrical primitive
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