International Association for Cryptologic Research

International Association
for Cryptologic Research

IACR News item: 16 June 2015

Iraklis Leontiadis, Kaoutar Elkhiyaoui, Refik Molvaa, Melek Onen ¨
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xisting work on data collection and analysis for aggregation is mainly

focused on confidentiality issues. That is, the untrusted Aggregator learns only the aggregation result without divulging individual data inputs. In this paper we extend the existing models with stronger security requirements. Apart from the privacy requirements with respect to the individual inputs we ask for unforgeability for the aggregate result. We first define the new security requirements of the model. We also instantiate a protocol for private and unforgeable aggregation for a non-interactive multi-party environment. I.e, multiple unsynchronized users owing to personal sensitive information without interacting with each other contribute their values in a secure way: The Aggregator learns the result of a function without learning individual values and moreover it constructs a proof that is forwarded to a verifier that will let the latter be convinced for the correctness of the computation. The verifier is restricted to not communicate with the users. Our protocol is provably secure in the random oracle model.

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