Contact Project Developer Ashish D. Tiwari [astiwz@gmail.com]
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Trust-but-Verify: Verifying Result Correctness of Outsourced Frequent Itemset Mining in Data-Mining-As-a-Service Paradigm

Cloud computing is popularizing the computing paradigm in which data is outsourced to a third-party service provider(server) for data mining.
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Abstract

Cloud computing is popularizing the computing paradigm in which data is outsourced to a third-party service provider(server) for data mining. Outsourcing, however, raises a serious security issue: how can the client of weak computational power verifythat the server returned correct mining result? In this paper, we focus on the specific task of frequent itemset mining. We consider theserver that is potentially untrusted and tries to escape from verification by using its prior knowledge of the outsourced data. We proposeefficient probabilistic and deterministic verification approaches to check whether the server has returned correct and complete frequentitemsets. Our probabilistic approach can catch incorrect results with high probability, while our deterministic approach measures theresult correctness with 100 percent certainty. We also design efficient verification methods for both cases that the data and the miningsetup are updated. We demonstrate the effectiveness and efficiency of our methods using an extensive set of empirical results on realdatasets.

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