Splitting anonymization: a novel privacy-preserving approach of social network
Splitting anonymization: a novel privacy-preserving approach of social network
复制标题
DOI：
10.1007/s10115-015-0855-2
复制
发表时间：
2015-07
影响因子：
2.7
通讯作者：
Yongjiao Sun;Ye Yuan;Guoren Wang;Yurong Cheng
中科院分区：
文献类型：
--
作者：
Yongjiao Sun;Ye Yuan;Guoren Wang;Yurong Cheng
由于社交网络技术和应用的快速发展，收集和发布了大量的个人社交信息，因此，对隐私进行保护和防止敏感信息泄露是非常必要的。目前的匿名化技术大多侧重于隐私保护，但即使价格较高，也不能准确地回答公用事业查询。为了解决这一问题，本文针对隐私与效用的矛盾，提出了一种新的匿名方法--分离式匿名。这种方法对攻击者未知的社交网络数据的隐私提供了高级别的保护，避免了由于对攻击者已知的知识进行强制噪声而导致的低效用。通过分裂匿名化处理的社交网络可以拒绝任何直接攻击，并且这些策略对于通常比直接攻击更危险的间接攻击也足够安全。最后，严格的理论分析和基于真实数据集的大量评价结果验证了本文的设计。
Large amount of personal social information is collected and published due to the rapid development of social network technologies and applications, and thus, it is quite essential to take privacy preservation and prevent sensitive information leakage. Most of current anonymizing techniques focus on the preservation to privacies, but cannot provide accurate answers to utility queries even at a high price. To solve the problem, a novel anonymizing approach, calledsplitting anonymization, is introduced in this paper to point against the contradiction of privacy and utility. This approach provides a high-level preservation to the privacy of social network data that is unknown to attackers, which avoids the low utility caused by the enforced noises on knowledge that is already known to the attackers. Social network processed by splitting anonymization can refuse any direct attack, and these strategies are also safe enough to indirect attacks which are usually more dangerous than direct attacks. Finally, strict theoretical analysis and large amount of evaluation results based on real data sets verified the design of this paper.