基于osn的隐私评分:作为潜在维度的共享数据粒度

IF 2.6 4区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

ACM Transactions on the Web Pub Date : 2023-06-17 DOI:10.1145/3604909

Yasir Kilic, Ali Inan

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引用次数: 0

摘要

隐私评分旨在基于用户的OSN个人资料页面中共享的属性值和用户在网络中的位置，测量用户在在线社交网络（OSN）上的隐私侵犯风险。现有的隐私评分研究依赖于可能存在偏见或情绪化的调查数据。在这项研究中，我们使用了从专业的领英OSN收集的真实世界数据，并表明从项目反应理论（IRT）导出的概率评分模型比天真的方法更适合真实世界的数据。我们还介绍了OSN用户在其个人资料上共享的数据粒度，作为OSN隐私评分问题的潜在维度。将数据粒度纳入我们的模型中，我们为OSN隐私评分问题构建了最全面的解决方案。对各种评分模型的广泛实验评估表明了所提出的解决方案的有效性。

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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Privacy Scoring Over OSNs: Shared Data Granularity as a Latent Dimension

Privacy scoring aims at measuring the privacy violation risk of a user over an online social network (OSN) based on attribute values shared in the user’s OSN profile page and the user’s position in the network. Existing studies on privacy scoring rely on possibly biased or emotional survey data. In this study, we work with real-world data collected from the professional LinkedIn OSN and show that probabilistic scoring models derived from the item response theory (IRT) fit real-world data better than naive approaches. We also introduce the granularity of the data an OSN user shares on her profile as a latent dimension of the OSN privacy scoring problem. Incorporating data granularity into our model, we build the most comprehensive solution to the OSN privacy scoring problem. Extensive experimental evaluation of various scoring models indicate the effectiveness of the proposed solution.

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来源期刊

ACM Transactions on the Web 工程技术-计算机：软件工程

CiteScore

4.90

自引率

0.00%

发文量

审稿时长

7.5 months

期刊介绍： Transactions on the Web (TWEB) is a journal publishing refereed articles reporting the results of research on Web content, applications, use, and related enabling technologies. Topics in the scope of TWEB include but are not limited to the following: Browsers and Web Interfaces; Electronic Commerce; Electronic Publishing; Hypertext and Hypermedia; Semantic Web; Web Engineering; Web Services; and Service-Oriented Computing XML. In addition, papers addressing the intersection of the following broader technologies with the Web are also in scope: Accessibility; Business Services Education; Knowledge Management and Representation; Mobility and pervasive computing; Performance and scalability; Recommender systems; Searching, Indexing, Classification, Retrieval and Querying, Data Mining and Analysis; Security and Privacy; and User Interfaces. Papers discussing specific Web technologies, applications, content generation and management and use are within scope. Also, papers describing novel applications of the web as well as papers on the underlying technologies are welcome.