TWC: Medium: Collaborative: Capturing People's Expectations of Privacy with Mobile Apps by Combining Automated Scanning and Crowdsourcing Techniques
TWC: Medium: Collaborative: Capturing People's Expectations of Privacy with Mobile Apps by Combining Automated Scanning and Crowdsourcing Techniques
批准号:
1228813
负责人:
Jason Hong
金额:
$80.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2016-08-31
中文摘要
我们的工作目标是:(a)以可扩展的方式捕捉人们在使用移动应用程序时的期望和惊喜,以及(b)以简单的格式总结这些看法,以帮助人们做出更好的信任决策。我们的主要想法是以人们对应用程序能做什么和不能做什么的期望的形式来分析隐私,重点关注应用程序在哪些方面打破了人们的期望。我们正在构建一个结合了自动扫描技术和众包的应用程序扫描仪。自动扫描捕获应用程序的行为,而众包用于解释这种行为的预期和可接受程度。这些信息是为应用程序构建更好的隐私摘要的基础。我们组织了一个跨学科的团队,在移动计算、计算机安全、系统和人机交互方面具有专业知识。这项工作的成功将包括:(a)应用程序扫描仪的设计和实现,该扫描仪将自动化技术与众包技术相结合,用于分析和解释移动应用程序与隐私相关的行为;(b)该应用程序扫描仪的一系列评估,显示有效性,准确性和可扩展性;(c)设计和评估更好的隐私摘要,优先考虑和突出应用程序最意想不到的行为;(d)展示了一种新的隐私概念,即隐私作为期望。成功还将帮助终端用户、企业和政府雇员更好地管理自己的隐私。
英文摘要
The goal of our work is to (a) capture people's expectations and surprises in using mobile apps in a scalable manner, and to (b) summarize these perceptions in a simple format to help people make better trust decisions. Our main idea is analyzing privacy in the form of people's expectations about what an app will and won't do, focusing on where an app breaks people's expectations. We are building an App Scanner that combines automated scanning techniques with crowdsourcing. Automated scanning captures the behavior of an app, while crowdsourcing is used to interpret how expected and acceptable this behavior is. This information is used as the basis for building a better privacy summary for apps. We have organized an interdisciplinary team with expertise in mobile computing, computer security, systems, and human-computer interaction.Success in this work will include results in: (a) the design and implementation of an App Scanner that combines automated techniques with crowdsourcing techniques for analyzing and interpreting privacy-related behaviors of mobile apps; (b) a series of evaluations of this app scanner, showing effectiveness, accuracy, and scalability; (c) the design and evaluation of better privacy summaries, which prioritize and highlight the most unexpected behaviors of an app; and (d) demonstration of a new conceptualization of privacy, namely privacy as expectations. Success will also help end-users, corporate and government employees manage their privacy better than can be done today.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
FAI: Organizing Crowd Audits to Detect Bias in Machine Learning
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批准号:2040942
-
项目类别:Standard Grant
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资助金额:$62.5万
-
财政年份:2021
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负责人:Jason Hong
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依托单位:
TWC: Small: CrowdVerify: Using the Crowd to Summarize Web Site Privacy Policies and Terms of Use Policies
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批准号:1422018
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项目类别:Standard Grant
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资助金额:$49.93万
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财政年份:2014
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负责人:Jason Hong
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依托单位:
EAGER: Social Cybersecurity: Applying Social Psychology to Improve Cybersecurity
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批准号:1347186
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项目类别:Standard Grant
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资助金额:$20.0万
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财政年份:2013
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负责人:Jason Hong
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依托单位:
SGER: Re-purposing Web Content through End-User Programming
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批准号:0646526
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2006
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负责人:Jason Hong
-
依托单位:
Next Generation Instant Messaging: Communication, Coordination, and Privacy for Mobile, Multimodal, and Location-Aware Devices
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批准号:0534406
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2006
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负责人:Jason Hong
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依托单位:
海外基金