Pivot: Privacy-Preserving Outsourcing of Text Data for Word Embedding Against Frequency Analysis Attack
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.
MSU Digital Commons Citation
Li, Yanying; Wang, Wendy Hui; and Dong, Boxiang, "Pivot: Privacy-Preserving Outsourcing of Text Data for Word Embedding Against Frequency Analysis Attack" (2019). Department of Computer Science Faculty Scholarship and Creative Works. 482.