International Association for Cryptologic Research

International Association
for Cryptologic Research

IACR News item: 16 June 2015

Iraklis Leontiadis, Kaoutar Elkhiyaoui, Refik Molva, Melek Önen
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Existing 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 unforge-

ability 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 con-

tribute 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 for-

warded 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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