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A Customized Text Sanitization Mechanism with Differential Privacy. (arXiv:2207.01193v2 [cs.CR] UPDATED)
cs.CR updates on arXiv.org arxiv.org
As privacy issues are receiving increasing attention within the Natural
Language Processing (NLP) community, numerous methods have been proposed to
sanitize texts subject to differential privacy. However, the state-of-the-art
text sanitization mechanisms based on metric local differential privacy (MLDP)
do not apply to non-metric semantic similarity measures and cannot achieve good
trade-offs between privacy and utility. To address the above limitations, we
propose a novel Customized Text (CusText) sanitization mechanism based on the
original $\epsilon$-differential privacy (DP) definition, which is …
art attention community differential privacy language local natural language natural language processing nlp non privacy similarity state text