海报:在线社交网络中保护隐私的个人资料相似度计算

Conference on Computer and Communications Security : proceedings of the ... conference on computer and communications security. ACM Conference on Computer and Communications Security Pub Date : 2011-10-17 DOI:10.1145/2046707.2093495

Arjan Jeckmans, Qiang Tang, P. Hartel

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引用次数: 9

摘要

目前，没有一个现有的在线社交网络(OSNs)允许其用户在不泄露私人信息的情况下结交新朋友。这让用户在寻找新朋友时处于弱势地位。我们提出了一种解决方案，使用户能够以保护隐私的方式计算她与另一个用户的个人资料相似度。我们的解决方案是针对实际的OSN环境设计的，不太可能出现一对用户同时在线的情况。

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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Poster: privacy-preserving profile similarity computation in online social networks

Currently, none of the existing online social networks (OSNs) enables its users to make new friends without revealing their private information. This leaves the users in a vulnerable position when searching for new friends. We propose a solution which enables a user to compute her profile similarity with another user in a privacy-preserving way. Our solution is designed for a realistic OSN environment, where a pair of users is unlikely to be online at the same time.

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来源期刊

Conference on Computer and Communications Security : proceedings of the ... conference on computer and communications security. ACM Conference on Computer and Communications Security

CiteScore

9.20

自引率

0.00%

发文量