VPASS:用于监控家庭语音命令的语音隐私助理系统
Bang Tran1, Sai Harshavardhan Reddy Kona1, Xiaohui Liang1
1Department of Computer Science, University of Massachusetts Boston, MA, USA.
概括
语音助理系统 (VAS) 可以暴露敏感数据. VPASS框架通过使用深度学习检测敏感语音命令来个性化隐私,保护用户信息.
科学领域:
- 人与计算机的交互
- 隐私工程 隐私工程 隐私工程
- 机器学习 机器学习
背景情况:
- 语音助理系统 (VAS) 提供了方便的交互,但由于敏感的语音数据,引发了隐私问题.
- 鉴别和管理敏感的语音命令是具有挑战性的,因为个性化和上下文隐私感知.
研究的目的:
- 引入VPASS,这是一个在VAS中管理个性化隐私要求的框架.
- 开发用于量化信息披露和语音命令隐私敏感性的机制.
- 为了能够准确地检测针对个人用户量身定制的对隐私敏感命令.
主要方法:
- 使用深度转移学习来处理语音命令.
- 量化信息披露和隐私敏感度等级.
- 利用个人交互历史进行个性化检测.
主要成果:
- 根据个性化的标准,准确检测隐私敏感的语音命令.
- VPASS有效量化信息披露和隐私敏感性.
- 该框架支持用户定义的隐私政策,以便量身定制的管理.
结论:
- VPASS为VAS中的个性化隐私管理提供了一个强大的解决方案.
- 拟议的机制提高了语音命令数据的安全性和隐私性.
- VPASS使用户能够更好地控制他们通过语音助理共享的敏感信息.
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