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P3S2: practical secure protocol for speech data publishing

Published: 17 May 2019 Publication History

Abstract

Speech data publishing discloses users' data privacy, and thus entails more privacy risks for users. Existing work sanitized the content, voice, and, voiceprint of speech data without considering the consistence among these three aspects, and therefore cannot protect users' data privacy. To this end, we propose a practical secure protocol for speech data publishing P3S2, the first attempt towards taking the corrections among the three factors into consideration when it sanitizes users' speech data. To concrete, it designs a three-dimension sanitization that utilizes feature learning to capture the set of characteristics in each dimension, and then sanitizes speech data in each dimension using the learned features. As a result, the correlations among the three dimensions of the sanitized speech data are guaranteed. Furthermore, it utilizes two real world datasets, TED talks and LibriSpeech to evaluate the performance of P3S2 in terms of the data privacy preservation.

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  1. P3S2: practical secure protocol for speech data publishing

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      cover image ACM Other conferences
      ACM TURC '19: Proceedings of the ACM Turing Celebration Conference - China
      May 2019
      963 pages
      ISBN:9781450371582
      DOI:10.1145/3321408
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 17 May 2019

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      Author Tags

      1. and data sanitization
      2. data privacy
      3. feature learning
      4. speech data publishing

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