CICI: RDP: Enforcing Security and Privacy Policies to Protect Research Data
CICI:RDP:执行安全和隐私政策以保护研究数据
基本信息
- 批准号:1920462
- 负责人:
- 金额:$ 92.45万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-08-01 至 2023-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Advances in computer systems over the past decade have laid a solid foundation for data collection at a staggering scale. Data generated from end-user devices has tremendous value to the research community. For example, mobile and Internet-of-Things devices can participate in large-scale Internet-based measurement or monitoring of patient's health conditions. While ground-breaking discovered may occur, malicious attacks or unintentional data leaks threaten the research data. Such a threat is hard to predict and difficult to recover from once it happens. Preventative and defensive measures should be taken where data is generated in order to protect private, valuable data from the attackers. Currently, there are efforts that try to regulate data management, for example, a research application might have a privacy policy that describes how the user data is being collected and protected. However, there is a disconnect between these documented policies and the implementations of a research project. In this project, the investigators propose to interpret the documented policies and enforce them in research projects, in order to protect the privacy of research data. This work can significantly reduce researchers' overhead in implementing policy-compliant code and reduce the complexity of protecting research datasets.In this project, the investigators provide a solution that protects research data using policies mandated by different regulatory entities, such as an application store and an Institutional Review Board (IRB). The system utilizes Natural Language Processing (NLP) techniques to extract security and privacy requirements from unstructured regulatory documents and translates these requirements to code that can patch a program that does not comply with the policies. The solution covers the lifetime of research data protection, from data collection to data storage, and data processing. This research has two thrusts. First, the investigators will build novel NLP techniques to extract security and privacy policies from unstructured, sparsely-labeled documents such as IRB protocols, and privacy disclosure of research applications. Second, the investigators will enforce these extracted policies in code, through context-aware program analysis to discover inconsistencies between a researcher's implementation and the extracted policies, and instrument researcher?s code to enforce compliant program behavior. The results of this work will have a transformative impact on the development of the next generation research data protection techniques, and more defensive security and privacy practices.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.
过去十年计算机系统的进步为大规模数据收集奠定了坚实的基础。从最终用户设备生成的数据对研究社区具有巨大价值。例如,移动的和物联网设备可以参与对患者健康状况的大规模基于互联网的测量或监测。虽然可能会发生突破性的发现,但恶意攻击或无意的数据泄露会威胁到研究数据。这种威胁很难预测,一旦发生就很难恢复。在生成数据的地方应该采取预防和防御措施,以保护私有的、有价值的数据免受攻击者的攻击。目前,有一些努力试图规范数据管理,例如,研究应用程序可能具有描述如何收集和保护用户数据的隐私策略。然而,这些成文的政策与研究项目的实施之间存在脱节。在这个项目中,研究人员建议解释记录的政策,并在研究项目中执行,以保护研究数据的隐私。这项工作可以大大减少研究人员在实施符合政策的代码时的开销,并降低保护研究数据集的复杂性。在该项目中,研究人员提供了一种解决方案,该解决方案使用不同监管实体(如应用程序商店和机构审查委员会(IRB))强制执行的策略来保护研究数据。该系统利用自然语言处理(NLP)技术从非结构化监管文件中提取安全和隐私要求,并将这些要求转换为代码,可以修补不符合政策的程序。该解决方案涵盖了研究数据保护的整个生命周期,从数据收集到数据存储和数据处理。这项研究有两个重点。首先,研究人员将建立新的NLP技术,从非结构化、稀疏标记的文档(如IRB协议)和研究应用程序的隐私披露中提取安全和隐私政策。其次,调查人员将执行这些提取的政策在代码中,通过上下文感知程序分析,以发现研究人员的实施和提取的政策之间的不一致,和仪器研究人员?的代码来强制兼容的程序行为。这项工作的成果将对下一代研究数据保护技术的发展产生变革性的影响,以及更具防御性的安全和隐私实践。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(11)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Findings: PolicyQA: A Reading Comprehension Dataset for Privacy Policies
研究结果:PolicyQA:隐私政策的阅读理解数据集
- DOI:
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Ahmad, A.;Chi, J.;Tian, Y.;Chang, K.
- 通讯作者:Chang, K.
Malware Family Classification via Residual Prefetch Artifacts
通过残留预取工件进行恶意软件家族分类
- DOI:10.1109/ccnc49033.2022.9700530
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Duby, Adam;Taylor, Teryl;Zhuang, Yanyan
- 通讯作者:Zhuang, Yanyan
Intent Classification and Slot Filling for Privacy Policies
- DOI:10.18653/v1/2021.acl-long.340
- 发表时间:2021-01
- 期刊:
- 影响因子:0
- 作者:Wasi Uddin Ahmad;Jianfeng Chi;Tu Le;Thomas B. Norton;Yuan Tian;Kai-Wei Chang
- 通讯作者:Wasi Uddin Ahmad;Jianfeng Chi;Tu Le;Thomas B. Norton;Yuan Tian;Kai-Wei Chang
OAUTHLINT: An Empirical Study on OAuth Bugs in Android Applications
- DOI:10.1109/ase.2019.00036
- 发表时间:2019-11
- 期刊:
- 影响因子:0
- 作者:Tamjid Al Rahat;Yu Feng;Yuan Tian
- 通讯作者:Tamjid Al Rahat;Yu Feng;Yuan Tian
Read Between the Lines: An Empirical Measurement of Sensitive Applications of Voice Personal Assistant Systems
- DOI:10.1145/3366423.3380179
- 发表时间:2020-04
- 期刊:
- 影响因子:0
- 作者:F. H. Shezan;Hang Hu;Jiamin Wang;Gang Wang;Yuan Tian
- 通讯作者:F. H. Shezan;Hang Hu;Jiamin Wang;Gang Wang;Yuan Tian
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Yuan Tian其他文献
Direct de/carboxylation of cannabidiolic acid (CBDA) and cannabidiol (CBD) from hemp plant material under supercritical CO2.
在超临界 CO2 下直接脱羧来自大麻植物材料的大麻二酚酸 (CBDA) 和大麻二酚 (CBD)。
- DOI:
10.1080/10286020.2024.2345825 - 发表时间:
2024 - 期刊:
- 影响因子:1.7
- 作者:
Baochang Gao;Yufeng Sun;Yuan Tian;Yu Shi;Zhi;Guoliang Mao - 通讯作者:
Guoliang Mao
Investigation on broadband propagation characteristic of terahertz electromagnetic wave in anisotropic magnetized plasma in frequency and time domain
太赫兹电磁波在各向异性磁化等离子体中频时域宽带传播特性研究
- DOI:
10.1063/1.4905227 - 发表时间:
2014-12 - 期刊:
- 影响因子:2.2
- 作者:
Yuan Tian;Xia Ai;Yiping Han;Xiuxiang Liu - 通讯作者:
Xiuxiang Liu
Mapping the drivers of formaldehyde (HCHO) variability from 2015 to 2019 over eastern China: insights from Fourier transform infrared observation and GEOS-Chem model simulation
绘制 2015 年至 2019 年中国东部甲醛 (HCHO) 变化的驱动因素:傅里叶变换红外观测和 GEOS-Chem 模型模拟的见解
- DOI:
10.5194/acp-21-6365-2021 - 发表时间:
2021-04 - 期刊:
- 影响因子:6.3
- 作者:
Youwen Sun;Hao Yin;Cheng Liu;Lin Zhang;Yuan Cheng;Mathias Palm;Justus Notholt;Xiao Lu;Corinne Vigouroux;Bo Zheng;Wei Wang;Nicholas Jones;Changong Shan;Min Qin;Yuan Tian;Qihou Hu;Fanhao Meng;Jianguo Liu - 通讯作者:
Jianguo Liu
Methyphenidate improves spatial memory of spontameously hypertensive rats:Evidence in behavioral and ultrastructural changes.
哌甲酯改善自发性高血压大鼠的空间记忆:行为和超微结构变化的证据。
- DOI:
- 发表时间:
- 期刊:
- 影响因子:2.5
- 作者:
Yuan Tian;Kiyoshi Maeda;Yaping Wang;Yongning Deng - 通讯作者:
Yongning Deng
Discovering Temporal Similarity Pattern Based on Metamorphosis Data
基于变形数据发现时间相似性模式
- DOI:
- 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
Yuan Tian - 通讯作者:
Yuan Tian
Yuan Tian的其他文献
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{{ truncateString('Yuan Tian', 18)}}的其他基金
Collaborative Research: Frameworks: MobilityNet: A Trustworthy CI Emulation Tool for Cross-Domain Mobility Data Generation and Sharing towards Multidisciplinary Innovations
协作研究:框架:MobilityNet:用于跨域移动数据生成和共享以实现多学科创新的值得信赖的 CI 仿真工具
- 批准号:
2411153 - 财政年份:2024
- 资助金额:
$ 92.45万 - 项目类别:
Standard Grant
Collaborative Research: DASS: Assessing the Relationship Between Privacy Regulations and Software Development to Improve Rulemaking and Compliance
合作研究:DASS:评估隐私法规与软件开发之间的关系以改进规则制定和合规性
- 批准号:
2317184 - 财政年份:2023
- 资助金额:
$ 92.45万 - 项目类别:
Standard Grant
Collaborative Research: SaTC: CORE: Medium: Toward safe, private, and secure home automation: from formal modeling to user evaluation
协作研究:SaTC:核心:中:迈向安全、私密和可靠的家庭自动化:从形式建模到用户评估
- 批准号:
2320903 - 财政年份:2022
- 资助金额:
$ 92.45万 - 项目类别:
Standard Grant
CICI: RDP: Enforcing Security and Privacy Policies to Protect Research Data
CICI:RDP:执行安全和隐私政策以保护研究数据
- 批准号:
2325369 - 财政年份:2022
- 资助金额:
$ 92.45万 - 项目类别:
Standard Grant
CAREER: Secure Voice-Controlled Platforms
职业:安全语音控制平台
- 批准号:
2323105 - 财政年份:2022
- 资助金额:
$ 92.45万 - 项目类别:
Continuing Grant
Collaborative Research: SaTC: CORE: Medium: Toward safe, private, and secure home automation: from formal modeling to user evaluation
协作研究:SaTC:核心:中:迈向安全、私密和可靠的家庭自动化:从形式建模到用户评估
- 批准号:
2114074 - 财政年份:2021
- 资助金额:
$ 92.45万 - 项目类别:
Standard Grant
CAREER: Secure Voice-Controlled Platforms
职业:安全语音控制平台
- 批准号:
1943100 - 财政年份:2020
- 资助金额:
$ 92.45万 - 项目类别:
Continuing Grant
CRII: SaTC: Improving the Usability and Effectiveness of Security and Privacy Settings in Mobile Apps
CRII:SaTC:提高移动应用程序中安全和隐私设置的可用性和有效性
- 批准号:
1850479 - 财政年份:2019
- 资助金额:
$ 92.45万 - 项目类别:
Standard Grant
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