Outsourcing collaborative filtering (CF) computations to the cloud helps handle large-scale data but raises concerns about result integrity. In this paper, we propose verification mechanisms for two widely used item-based CF methods. By applying game theory, we analyze potential cheating by cloud providers and show how the right incentives can ensure honest behavior. Our approach offers a practical, efficient solution to secure outsourced CF computations.
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