Publicly Verifiable Grouped Aggregation Queries on Outsourced Data Streams - Nath, Suman; Venkatesan, Ramarathnam (ICDE'13: 29th IEEE International Conference on Data Engineering, 2013)
Outsourcing data streams and desired computations to a third party such as the cloud is a desirable option to many companies. However, data outsourcing and remote computations intrinsically raise issues of trust, making it crucial to verify results returned by third parties. In this context, we propose a novel solution to verify outsourced grouped aggregation queries (e.g., histogram or SQL Group-by queries) that are common in many business applications. We consider a setting where a data owner employs an untrusted remote server to run continuous grouped aggregation queries on a data stream it forwards to the server. Untrusted clients then query the server for results and efficiently verify correctness of the results by using a small and easy-to-compute signature provided by the data owner. Our work complements previous works on authenticating remote computation of selection and aggregation queries. The most important aspect of our solution is that it is publicly verifiable—unlike most prior works, we support untrusted clients (who can collude with other clients or with the server). Experimental results on real and synthetic data show that our solution is practical and efficient.