Abstract
In this paper, we focus our attention on the problem of Gibbs sampling for privacy-preserving Latent Dirichlet Allocation, which is equals to a problem of computing the ratio of two numbers, both of which are the summations of the private numbers distributed in different parties. Such a problem has been studied in the case that each party is semi-honest. Here we propose a new solution based on a weaken assumption that some of the parties may collaborate together to extract information of other parties.
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Yang, B., Nakagawa, H. (2010). Computation of Ratios of Secure Summations in Multi-party Privacy-Preserving Latent Dirichlet Allocation. In: Zaki, M.J., Yu, J.X., Ravindran, B., Pudi, V. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2010. Lecture Notes in Computer Science(), vol 6118. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13657-3_22
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DOI: https://doi.org/10.1007/978-3-642-13657-3_22
Publisher Name: Springer, Berlin, Heidelberg
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