EAGER: TWC: Collaborative: iPrivacy: Automatic Recommendation of Personalized Privacy Settings for Image Sharing

EAGER：TWC：协作：iPrivacy：自动推荐图像共享的个性化隐私设置

基本信息

批准号：
1651455
负责人：
Dan Lin
金额：
$ 14.49万
依托单位：
Missouri University of Science and Technology
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-01 至 2018-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1651455&HistoricalAwards=false
关键词：
EAGER TWC Collaborative iPrivacy Automatic

项目摘要

The objective of this project is to investigate a comprehensive image privacy recommendation system, called iPrivacy (image Privacy), which can efficiently and automatically generate proper privacy settings for newly shared photos that also considers consensus of multiple parties appearing in the same photo. Photo sharing has become very popular with the growing ubiquity of smartphones and other mobile devices. However, many people especially young users of social networks often share private photos about themselves and their friends without being aware of the potential impact on their future lives caused by unwanted disclosure and privacy violations. Although some photo sharing platforms start to offering functions of privacy configuration, such manual process could be very tedious for users and also error-prone since not many users have sufficient background knowledge about privacy. This project will address these rising privacy concerns of photo sharing in social sites and benefit billions of social network users. The broader impact of this project will be further enhanced by the integration of education and research. A range of educational activities will be carried out including curriculum development, professional training for students and cybersecurity camp for K-12 teachers, with emphasis to under-represented groups.This project will seamlessly integrate expertise from two different domains: image understanding and privacy management, leading to one of the first comprehensive and automatic policy recommendation systems. The proposed project contains the following innovative researches. First, a multi-party privacy-sensitive object identification algorithm will be developed which will be capable of automatically generating the identity of each human subject in a photo so as to automate the subsequent privacy harmonization process. Second, a unique privacy harmonization approach will be designed, which will conduct hierarchical privacy policy mining to understand different levels of privacy concerns in communities, recommend policies that effectively harmonize privacy preferences of multiple people appearing in the same photo and also adapt to the evolution of people's privacy preferences. The proposed iPrivacy system will not only fully release the burden of privacy configuration at users' side, but will also promote better privacy practice based on knowledge learned from large-scale historical and societal information.

该项目的目的是研究一个称为Iprivacy（图像隐私）的综合图像隐私建议系统，该系统可以有效，自动为新共享的照片生成适当的隐私设置，该照片还考虑了同一照片中出现多个方的共识。随着智能手机和其他移动设备的普遍存在，照片共享变得非常受欢迎。但是，许多人尤其是社交网络的年轻用户经常分享有关自己和朋友的私人照片，而不会意识到因不必要的披露和侵犯隐私而导致的未来生活的潜在影响。尽管某些照片共享平台开始提供隐私配置功能，但这种手动过程可能非常乏味，并且由于没有很多用户对隐私有足够的背景知识。该项目将解决社交网站中照片共享的这些不断上升的隐私问题，并使数十亿个社交网络用户受益。通过教育和研究的整合将进一步增强该项目的更广泛影响。将进行一系列教育活动，包括课程开发，针对学生的专业培训以及针对K-12教师的网络安全训练营，重点是代表性不足的小组。该项目将无缝地从两个不同的领域中无缝整合图像理解和隐私管理的专业知识：导致第一个综合和自动政策建议系统中的一种。拟议的项目包含以下创新研究。首先，将开发多方隐私对象识别算法，该算法将能够自动在照片中生成每个人类主体的身份，从而自动化随后的隐私协调过程。其次，将设计一种独特的隐私协调方法，该方法将进行层次的隐私政策挖掘以了解社区中不同级别的隐私问题，建议有效地协调同一照片中多人的隐私偏好的政策，并适应人们的隐私偏好的演变。拟议的Iprivacy系统不仅将在用户方面完全释放隐私配置的负担，而且还将根据从大规模的历史和社会信息中学到的知识来促进更好的隐私实践。