End-to-end aggregate authentication of time-series data

We consider the problem of providing integrity of aggregate result in the presence of an untrusted data aggregator who may introduce errors into data fusion, causing the final aggregate result to far deviate from the true result determined by participating values. We proposes a construction that allows a group of participants to periodically upload authenticated data values to a data aggregator, such that the aggregator is able to derive an aggregate signature over the true aggregate result, but is unable to do so if any error is introduced into the aggregate result. To our knowledge, it is the first secure agggregate authentication scheme that achieves end-to-end security without resorting to additional communication or third parties. Our construction supports iterative aggregation thus it can be used in a networked environment where there exists multi-level of aggregators. Our construction is efficient in term of both computation and communication. Especially, the online computation cost of aggregate tag verification is constant and independent of the number of underlying individual signatures. We prove the security of our construction under the assumption of CDH problem.

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