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.
| Original language | English |
|---|---|
| Pages (from-to) | 77-79 |
| Number of pages | 3 |
| Journal | CEUR Workshop Proceedings |
| Volume | 2335 |
| State | Published - 2019 |
| Event | 2019 PAL: Privacy-Enhancing Artificial Intelligence and Language Technologies, PAL 2019 - Palo Alto, United States Duration: 25 Mar 2019 → 27 Mar 2019 |