From Tag to Protect: A Tag-Driven Policy Recommender System for Image Sharing
From Tag to Protect: A Tag-Driven Policy Recommender System for Image Sharing
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DOI：
10.1109/pst.2017.00047
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发表时间：
2017-08
期刊：
影响因子：
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通讯作者：
A. Squicciarini;Andrea Novelli;D. Lin;Cornelia Caragea;Haoti Zhong
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文献类型：
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作者：
A. Squicciarini;Andrea Novelli;D. Lin;Cornelia Caragea;Haoti Zhong
在社交网站上分享图像已成为越来越多在线用户日常生活的一部分。然而，面对在线共享的大量图像，对于一个人来说，为他/她上传的每张图像手动配置适当的隐私设置并不是一项简单的任务。图像共享过程中缺乏适当的隐私保护可能会导致人们的私生活受到许多潜在的隐私侵犯，而他们却没有意识到。在这项工作中，我们提出了一个隐私设置推荐系统，以帮助人们轻松地为其在线图像设置隐私设置。关键思想是基于我们的发现而提出的，即无论图像所有者的个人隐私偏见和意识水平如何，图像隐私设置和图像标签的许多通用模式之间都存在一定的相关性。我们提出了一种多管齐下的机制，仔细分析标签的语义和共存性，为新上传的图像导出一组合适的隐私设置。当可用图像标签很少时，我们的系统还能够处理冷启动问题。我们进行了广泛的实验研究，结果证明了我们的方法在政策建议准确性方面的有效性。
Sharing images on social network sites has become a part of daily routine for more and more online users. However, in face of the considerable amount of images shared online, it is not a trivial task for a person to manually configure proper privacy settings for each of the images that he/she uploaded. The lack of proper privacy protection during image sharing could raise many potential privacy breaches of people's private lives that they are not aware of. In this work, we propose a privacy setting recommender system to help people effortlessly set up the privacy settings for their online images. The key idea is developed based on our finding that there are certain correlations between a number of generic patterns of image privacy settings and image tags, regardless of the image owners' individual privacy bias and levels of awareness. We propose a multi-pronged mechanism that carefully analyzes tags' semantics and co-presence to derive a set of suitable privacy settings for a newly uploaded image. Our system is also capable of dealing with cold-start problem when there are very few image tags available. We have conducted extensive experimental studies and the results demonstrate the effectiveness of our approach in terms of the policy recommendation accuracy.