User Centric Policy Management in Online Social Networks

Mohamed Shehab, Gorrell P. Cheek, Hakim Touati, A. Squicciarini, P. Cheng
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引用次数: 22

Abstract

Online social networking sites are experiencing tremendous user growth with hundreds of millions of active users. As a result, there is a tremendous amount of user profile data online, e.g., name, birth date, etc. Protecting this data is a challenge. The task of access policy composition is a tedious and confusing effort for the average user having hundreds of friends. In this paper, we propose a Policy Manager (PolicyMgr) Framework for social networks. PolicyMgr assists users in composing and managing their access control policies for objects posted to their profiles. Our approach is based on a supervised learning mechanism that leverages user provided example policy settings as training sets to build classifiers that are the basis for auto-generated policies. Furthermore, we provide mechanisms to enable users to fuse policy decisions that are provided by their friends or others in the social network. These policies then regulate access to user profile objects. We implemented our framework and, through experimentation, demonstrate positive emerging results.
在线社交网络中以用户为中心的策略管理
在线社交网站正经历着用户的巨大增长,活跃用户已达数亿。因此,网上有大量的用户资料数据,如姓名、出生日期等。保护这些数据是一项挑战。对于拥有数百个朋友的普通用户来说,组合访问策略是一项乏味而令人困惑的工作。在本文中,我们提出了一个针对社交网络的策略管理器(policygr)框架。policygr帮助用户编写和管理发布到其配置文件的对象的访问控制策略。我们的方法基于监督学习机制,该机制利用用户提供的示例策略设置作为训练集来构建分类器,这些分类器是自动生成策略的基础。此外,我们还提供了一些机制,使用户能够融合他们的朋友或社交网络中的其他人提供的政策决策。然后,这些策略规范对用户配置文件对象的访问。我们实施了我们的框架,并通过实验展示了积极的新结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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