Title

Pivot: Privacy-Preserving Outsourcing of Text Data for Word Embedding Against Frequency Analysis Attack

Document Type

Conference Proceeding

Publication Date

1-1-2019

Abstract

In this paper, we design PIVOT, a new privacy-preserving method that supports outsourcing of text data for word embedding. PIVOT includes a 1-to-many mapping function for text documents that can defend against the frequency analysis attack with provable guarantee, while preserving the word context during transformation.

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