Verifying Result Correctness of Outsourced Frequent Itemset in Data Mining through Probabilistic and deterministic approaches
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 8
Abstract
Cloud computing technology has enabled large organization to outsource data to a third-party service provider (server) for data mining and has provided a natural solution for the data-mining paradigms. However, outsourcing raises a serious security and privacy issue. Data outsourcing is the key task in recent days, for accessing services of the database processing. For the client with the weak computational capacity, there is no assurance or guarantee to know if the server returned correct mining results or not. This paper focuses on the specific task of frequent item set mining. The server that is potentially untrusted and tries to escape from verification by using its prior knowledge of the outsourced data is considered. An efficient probabilistic and deterministic verification approach to check whether the server has returned correct and complete frequent item sets is proposed. This proposed verification approach can catch incorrect results with high probability and the deterministic approach measures the result correctness with 100% certainty. The result shows that the proposed efficient verification method is desirable for both the cases. And the effectiveness and efficiency of our method gives secure and faster results using an extensive set of empirical results on real datasets.
Authors and Affiliations
Dr. P. Julia Grace, Vanitha Suresh
Keywords
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- EP ID EP392017
- DOI 10.9790/9622-0708035659.
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