Learnable audio encryption for untrusted outsourcing machine learning services

Po Wen Chi, Pin Hsin Hsiao

研究成果: 書貢獻/報告類型會議論文篇章

摘要

Applying machine learning to problems has become an avoidable trend. With the help of machine learning techniques, people can make predictions more accurately and can get more benefits. However, the machine learning technique relies on training from lots of data. That is, data should be open to the machine learning service provider. Considering the user privacy issue, the release of user data is not acceptable. In this paper, we propose an approach to take care both the machine learning feature and the data privacy. We focus on audio data and propose an audio encryption technique to keep audio data credential. In the meantime, we make the encrypted audio be able to be trained though machine learning service providers.

原文英語
主出版物標題Proceedings - 2019 14th Asia Joint Conference on Information Security, AsiaJCIS 2019
發行者Institute of Electrical and Electronics Engineers Inc.
頁面151-156
頁數6
ISBN(電子)9781728125565
DOIs
出版狀態已發佈 - 2019 八月
事件14th Annual Asia Joint Conference on Information Security, AsiaJCIS 2019 - Kobe, 日本
持續時間: 2019 八月 12019 八月 2

出版系列

名字Proceedings - 2019 14th Asia Joint Conference on Information Security, AsiaJCIS 2019

會議

會議14th Annual Asia Joint Conference on Information Security, AsiaJCIS 2019
國家/地區日本
城市Kobe
期間2019/08/012019/08/02

ASJC Scopus subject areas

  • 軟體
  • 資訊系統與管理
  • 電腦網路與通信
  • 安全、風險、可靠性和品質

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