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Finding frequent itemsets is the most costly task in association rule mining. Outsourcing this task to a service provider brings several benefits to the data owner such as cost relief and a less commitment to storage and computational resources. Mining results, however, can be corrupted if the service provider is honest but makes mistakes in the mining process, or is lazy and reduces costly computation, returning incomplete results, or is malicious and contaminates the mining results. The authors address the integrity issue in the outsourcing process, i.e., how the data owner verifies the correctness of the mining results. For this purpose, they propose and develop an audit environment, which consists of a database transformation method and a result verification method.
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