CAREER: Secure Voice-Controlled Platforms

职业：安全语音控制平台

• 批准号: 1943100
• 负责人: Yuan Tian
• 金额: $ 49.04万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1943100&HistoricalAwards=false
• 关键词: CAREER; Secure; Voice; Controlled; Platforms

Voice control technologies, which utilize natural language processing (NLP) techniques to enable handsfree interactions through Voice User Interface (VUI), are widely deployed in a plethora of IoT platforms, such as Amazon Alexa, Google Home, and automotive voice assistants. In addition to the built-in functionalities, voice-controlled devices are enhanced by an ecosystem fostered by their providers, such as Amazon and Google. In such an ecosystem, third-party developers can build new functions to offer additional services to the end-users for example, order food, manage bank accounts, and lock doors. These systems have already been deployed to households around the world and utilized by tens of millions of users. However, they could bring in new security and privacy risks, whose implications are not adequately understood so far. This work focuses on addressing the security and privacy issues in voice-controlled platforms. The project defines how we secure users while using voice interfaces and make key progress towards securing the IoT infrastructure and enhancing national security. Combined with integrated education and outreach efforts, this work provides a technical foundation for designing IoT platforms with strong security and privacy properties. Protecting Voice User Interfaces is fundamentally challenging, owing to the lack of effective means to authenticate and authorize the parties involved in the open and noisy channel. The project focuses on protecting users by helping them avoid unexpected sensitive behaviors through the noisy, open, and low-bandwidth voice channel. The work is organized around three main thrusts: (1) the design of a chatbot-based effective and efficient testing framework that combines semantic understanding and security domain knowledge to generate inputs, and understands outputs for determining unexpected sensitive behaviors in the voice apps during installation time, (2) the design of context-based integrity check and detection for unexpected voice command at runtime, and (3) the design of usable interfaces to communicate with users about the risks identified in the first two thrusts. These explorations culminate in the design options for a security module as part of a voice-controlled platform, and broader security and privacy recommendations for IoT platforms.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.

语音控制技术利用自然语言处理（NLP）技术通过语音用户界面（VUI）实现免提交互，广泛部署在众多物联网平台中，如Amazon Alexa、Google Home和汽车语音助手。除了内置的功能外，语音控制设备还通过亚马逊和谷歌等提供商培育的生态系统进行了增强。在这样的生态系统中，第三方开发人员可以构建新的功能，为最终用户提供额外的服务，例如订购食物，管理银行账户和锁门。这些系统已经部署到世界各地的家庭，并被数千万用户使用。然而，它们可能带来新的安全和隐私风险，其影响迄今尚未得到充分理解。这项工作的重点是解决语音控制平台中的安全和隐私问题。该项目定义了我们如何在使用语音接口的同时保护用户，并在保护物联网基础设施和增强国家安全方面取得了关键进展。结合综合教育和推广工作，这项工作为设计具有强大安全性和隐私特性的物联网平台提供了技术基础。保护语音用户界面从根本上说是一项挑战，因为缺乏有效的手段来验证和授权参与开放和嘈杂信道的各方。该项目的重点是保护用户，帮助他们避免通过嘈杂，开放和低带宽的语音通道进行意外的敏感行为。这项工作围绕三个主要方面展开：（1）基于聊天机器人的有效且高效的测试框架的设计，该框架结合语义理解和安全领域知识来生成输入，并且理解输出，以用于在安装时间期间确定语音应用中的意外敏感行为，（2）基于上下文的完整性检查和检测的设计，以用于在运行时的意外语音命令，以及（3）设计可用的界面，以与用户就前两个重点中识别的风险进行沟通。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响力审查标准进行评估，被认为值得支持。

项目成果

Trade-offs and Guarantees on Adversarial Representation Learning for Information Obfuscation

信息混淆的对抗性表示学习的权衡和保证

• 发表时间: 2020
• 期刊: Advances in neural information processing systems
• 作者: Zhao, H.;Chi, J.;Tian, Y.;Gordon., J.
• 通讯作者: Gordon., J.

Towards Return Parity in Markov Decision Processes

• 发表时间: 2021-11
• 作者: Jianfeng Chi;Jian Shen;Xinyi Dai;Weinan Zhang;Yuan Tian;Han Zhao

Intent Classification and Slot Filling for Privacy Policies

• DOI: 10.18653/v1/2021.acl-long.340
• 发表时间: 2021-01
• 作者: Wasi Uddin Ahmad;Jianfeng Chi;Tu Le;Thomas B. Norton;Yuan Tian;Kai-Wei Chang

Your Microphone Array Retains Your Identity: A Robust Voice Liveness Detection System for Smart Speakers

• 发表时间: 2022
• 作者: Yan Meng;Jiachun Li;Matthew Pillari;A. Deopujari;Liam Brennan;Hafsah Shamsie;Haojin Zhu;Yuan Tian