کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
383547 660826 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Enforcing transparent access to private content in social networks by means of automatic sanitization
ترجمه فارسی عنوان
اجرای دسترسی شفاف به محتوای خصوصی در شبکه های اجتماعی با استفاده از سانسورگرایی اتوماتیک
کلمات کلیدی
نشر داده؛ حفاظت از داده ها؛ شبکه های اجتماعی؛ سانسورگرایی متن؛ حریم خصوصی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• A system to enforce privacy protection in existing social networks.
• An automatic method to assess the privacy risks of users’ publications.
• A transparent data storage and accessing mechanism according to users’ credentials.
• Feasibility study and two illustrative case studies.

Social networks have become an essential meeting point for millions of individuals willing to publish and consume huge quantities of heterogeneous information. Some studies have shown that the data published in these platforms may contain sensitive personal information and that external entities can gather and exploit this knowledge for their own benefit. Even though some methods to preserve the privacy of social networks users have been proposed, they generally apply rigid access control measures to the protected content and, even worse, they do not enable the users to understand which contents are sensitive. Last but not least, most of them require the collaboration of social network operators or they fail to provide a practical solution capable of working with well-known and already deployed social platforms. In this paper, we propose a new scheme that addresses all these issues. The new system is envisaged as an independent piece of software that does not depend on the social network in use and that can be transparently applied to most existing ones. According to a set of privacy requirements intuitively defined by the users of a social network, the proposed scheme is able to: (i) automatically detect sensitive data in users’ publications; (ii) construct sanitized versions of such data; and (iii) provide privacy-preserving transparent access to sensitive contents by disclosing more or less information to readers according to their credentials toward the owner of the publications. We also study the applicability of the proposed system in general and illustrate its behavior in two case studies.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 62, 15 November 2016, Pages 148–160
نویسندگان
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