Yaowei Han, Yang Cao, Sheng Li, Qiang Ma, Masatoshi Yoshikawa
{"title":"声音不可分辨——在不可信服务器下保护声纹的差异隐私","authors":"Yaowei Han, Yang Cao, Sheng Li, Qiang Ma, Masatoshi Yoshikawa","doi":"10.1145/3372297.3420025","DOIUrl":null,"url":null,"abstract":"With the rising adoption of advanced voice-based technology together with increasing consumer demand for smart devices, voice-controlled \"virtual assistants\" such as Apple's Siri and Google Assistant have been integrated into people's daily lives. However, privacy and security concerns may hinder the development of such voice-based applications since speech data contain the speaker's biometric identifier, i.e., voiceprint (as analogous to fingerprint). To alleviate privacy concerns in speech data collection, we propose a fast speech data de-identification system that allows a user to share her speech data with formal privacy guarantee to an untrusted server. Our open-sourced system can be easily integrated into other speech processing systems for collecting users' voice data in a privacy-preserving way. Experiments on public datasets verify the effectiveness and efficiency of the proposed system.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"100 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Voice-Indistinguishability -- Protecting Voiceprint with Differential Privacy under an Untrusted Server\",\"authors\":\"Yaowei Han, Yang Cao, Sheng Li, Qiang Ma, Masatoshi Yoshikawa\",\"doi\":\"10.1145/3372297.3420025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rising adoption of advanced voice-based technology together with increasing consumer demand for smart devices, voice-controlled \\\"virtual assistants\\\" such as Apple's Siri and Google Assistant have been integrated into people's daily lives. However, privacy and security concerns may hinder the development of such voice-based applications since speech data contain the speaker's biometric identifier, i.e., voiceprint (as analogous to fingerprint). To alleviate privacy concerns in speech data collection, we propose a fast speech data de-identification system that allows a user to share her speech data with formal privacy guarantee to an untrusted server. Our open-sourced system can be easily integrated into other speech processing systems for collecting users' voice data in a privacy-preserving way. Experiments on public datasets verify the effectiveness and efficiency of the proposed system.\",\"PeriodicalId\":20481,\"journal\":{\"name\":\"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security\",\"volume\":\"100 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3372297.3420025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3372297.3420025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Voice-Indistinguishability -- Protecting Voiceprint with Differential Privacy under an Untrusted Server
With the rising adoption of advanced voice-based technology together with increasing consumer demand for smart devices, voice-controlled "virtual assistants" such as Apple's Siri and Google Assistant have been integrated into people's daily lives. However, privacy and security concerns may hinder the development of such voice-based applications since speech data contain the speaker's biometric identifier, i.e., voiceprint (as analogous to fingerprint). To alleviate privacy concerns in speech data collection, we propose a fast speech data de-identification system that allows a user to share her speech data with formal privacy guarantee to an untrusted server. Our open-sourced system can be easily integrated into other speech processing systems for collecting users' voice data in a privacy-preserving way. Experiments on public datasets verify the effectiveness and efficiency of the proposed system.