Abstract. With the advent of networking applications collecting user data on a massive scale, the privacy of individual users appears to be a major concern. The main challenge is the design of a solution that allows the data analyzer to compute global statistics over the set of individual inputs that are protected by some confidentiality mechanism. Joye et al. [7] recently suggested a solution that allows a centralized party to compute the sum of encrypted inputs collected through a smart metering network. The main shortcomings of this solution are
its reliance on a trusted dealer for key distribution and the need for frequent key
updates. In this paper we introduce a secure protocol for aggregation of time series
data that is based on the Joye et al. [7] scheme and in which the main
shortcomings of the latter, namely, the requirement for key updates and for the
trusted dealer are eliminated. Moreover our scheme supports a dynamic group
management, whereby as opposed to Joye et al. [7] leave and join operations do
not trigger a key update at the users.
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