CAREER: Ensuring Privacy, Inclusiveness, and Policy Compliance in the Era of Voice Personal Assistants

职业:确保语音个人助理时代的隐私、包容性和政策合规性

基本信息

  • 批准号:
    2239605
  • 负责人:
  • 金额:
    $ 50.25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-08-01 至 2028-07-31
  • 项目状态:
    未结题

项目摘要

Voice personal assistants such as Amazon Alexa and Google Assistant are rapidly gaining in both domestic and business popularity. Despite many convenient features they provide, concerns have been raised about the security and privacy, and content safety related risks to end users they also pose. During the interaction with voice assistants, users expect the voice assistants to fulfill their requests without compromising the privacy or being exposed to unsafe content, and without experiencing racial or gender disparities in terms of the automated speech recognition. The project’s novelties are new techniques and mechanisms to ensure privacy, inclusiveness, and policy compliance in voice assistant systems. The project's broader significance and importance include 1) increasing general awareness of cybersecurity in the K-12 community through various outreach and educational activities; 2) training the next generation of cybersecurity researchers especially underrepresented and minorities; and 3) strengthening cybersecurity education by developing new course materials and hands-on labs.This project first develops a voice-based privacy notice mechanism to enable users (in particular, visually impaired users) to make informed privacy decisions through the voice channel. It creates a new paradigm for accessible and inclusive privacy notification. This project then proposes a machine learning-based dynamic analysis framework, which allows a systematic evaluation of policy compliance and social biases in voice assistant systems. It can be used by users to check for any privacy or content safety violations in voice applications, and can potentially aid government agencies to perform a large-scale investigation into the policy compliance practices of existing voice applications in the Amazon Alexa and Google Assistant platforms. Finally, this project develops static analysis techniques to assist developers in producing policy-compliant voice applications at the development phase. This project also integrates a comprehensive education and outreach plan with the proposed research to train the next generation of cybersecurity researchers in an interdisciplinary environment, and to attract more students from underrepresented groups into the cybersecurity field.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
亚马逊Alexa和谷歌助手等语音个人助理在国内和企业中的普及率都在迅速上升。尽管它们提供了许多方便的功能,但它们也对最终用户带来了安全和隐私以及内容安全相关风险的担忧。在与语音助手的交互期间,用户期望语音助手在不损害隐私或暴露于不安全内容的情况下满足他们的请求,并且在自动语音识别方面不会经历种族或性别差异。该项目的创新之处在于新技术和机制,以确保语音助理系统的隐私性、包容性和政策合规性。该项目更广泛的意义和重要性包括:1)通过各种宣传和教育活动,提高K-12社区对网络安全的普遍认识; 2)培训下一代网络安全研究人员,特别是代表性不足和少数民族; 3)通过开发新的课程材料和动手实验室加强网络安全教育。该项目首先开发了一个语音-基于隐私通知机制,使用户(特别是视障用户)能够通过语音通道做出知情的隐私决定。它为可访问和包容性的隐私通知创建了一个新的范例。然后,该项目提出了一个基于机器学习的动态分析框架,该框架允许系统地评估语音助理系统中的政策遵从性和社会偏见。用户可以使用它来检查语音应用程序中的任何隐私或内容安全违规行为,并可能帮助政府机构对亚马逊Alexa和Google Assistant平台中现有语音应用程序的政策合规性做法进行大规模调查。最后,本项目开发静态分析技术,以帮助开发人员在开发阶段产生符合政策的语音应用程序。该项目还整合了一个全面的教育和推广计划与拟议的研究,以培养下一代网络安全研究人员在跨学科的环境中,并吸引更多的学生从代表性不足的群体进入网络安全领域。该奖项反映了NSF的法定使命,并已被认为是值得支持的评估使用基金会的智力价值和更广泛的影响审查标准。

项目成果

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会议论文数量(0)
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Long Cheng其他文献

Real-Time Underwater Onboard Vision Sensing System for Robotic Gripping
用于机器人抓取的实时水下机载视觉传感系统
Effect of helium pre-implantation on the thermal shock performance of tungsten
预注入氦气对钨热震性能的影响
  • DOI:
    10.1016/j.nme.2021.100934
  • 发表时间:
    2021-02
  • 期刊:
  • 影响因子:
    2.6
  • 作者:
    Yingdi Wang;Wangguo Guo;Yida Zhu;Yue Yuan;Zheng Wang;Long Cheng;Zhe Chen;Youyun Lian;Xiang Liu;Guang-Hong Lv
  • 通讯作者:
    Guang-Hong Lv
Effect of SiO2 grafted MWCNTs on the mechanical and dielectric properties of PEN composite films
SiO2接枝MWCNT对PEN复合薄膜力学和介电性能的影响
  • DOI:
    10.1016/j.apsusc.2015.09.086
  • 发表时间:
    2015-12
  • 期刊:
  • 影响因子:
    6.7
  • 作者:
    Jin Fei;Feng Mengna;Huang Xu;Long Cheng;Jia Kun;Liu Xiaobo
  • 通讯作者:
    Liu Xiaobo
Martian Bow Shock Oscillations Driven by Solar Wind Variations: Simultaneous Observations From Tianwen‐1 and MAVEN
太阳风变化驱动的火星弓激波振荡:天问一号和 MAVEN 的同步观测
  • DOI:
    10.1029/2023gl104769
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    5.2
  • 作者:
    Long Cheng;R. Lillis;Yuming Wang;A. Mittelholz;Shaosui Xu;D. Mitchell;C. Johnson;Z. Su;J. Halekas;B. Langlais;Tielong Zhang;Guoqiang Wang;S. Xiao;Zhuxuan Zou;Zhiyong Wu;Y. Chi;Z. Pan;Kai Liu;X. Hao;Yiren Li;Manming Chen;J. Espley;F. Eparvier
  • 通讯作者:
    F. Eparvier
Influence of neon seeding on the deuterium retention and surface modification of ITER-like forged tungsten
氖籽晶对类ITER锻造钨的氘保留和表面改性的影响
  • DOI:
    10.1088/1741-4326/abbc86
  • 发表时间:
    2020-11
  • 期刊:
  • 影响因子:
    3.3
  • 作者:
    Yue Yuan;Ting Wang;Arkadi Kreter;Michael Reinhart;Alexis Terra;Sören Möller;Long Cheng;Christian Linsmeier;Guang-Hong Lu
  • 通讯作者:
    Guang-Hong Lu

Long Cheng的其他文献

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{{ truncateString('Long Cheng', 18)}}的其他基金

Collaborative Research: SAI-R: Integrative Cyberinfrastructure for Enhancing and Accelerating Online Abuse Research
合作研究:SAI-R:用于加强和加速在线滥用研究的综合网络基础设施
  • 批准号:
    2228616
  • 财政年份:
    2022
  • 资助金额:
    $ 50.25万
  • 项目类别:
    Standard Grant
Collaborative Research: EAGER: SaTC-EDU: Learning Platform and Education Curriculum for Artificial Intelligence-Driven Socially-Relevant Cybersecurity
合作研究:EAGER:SaTC-EDU:人工智能驱动的社会相关网络安全的学习平台和教育课程
  • 批准号:
    2114920
  • 财政年份:
    2021
  • 资助金额:
    $ 50.25万
  • 项目类别:
    Standard Grant

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CNS 核心:小型:通过固态存储设备的运行时模拟清理确保隐私
  • 批准号:
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Ensuring Data Privacy in Deep Learning through Compressive Learning
通过压缩学习确保深度学习中的数据隐私
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SaTC: CORE: Medium: Privacy for All: Ensuring Fair Privacy Protection in Machine Learning
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具有隐私保护功能的身份验证协议,确保无接收性、抗胁迫性和可否认性
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