【摘要】 近年来,社会网络中的隐私保护得到了诸多关注。攻击者可以应用相关背景知识对发布的社会网络进行攻击,从而导致用户的隐私被泄露。已有工作通常只考虑了结点泄露和边泄露的情况,而忽略了攻击者可能通过识别用户的敏感信息来进行攻击。针对现有问题,提出了特征泄露的概念,并进行了理论分析。在此基础上,创造性地提出了三级隐私保护的概念,建立了隐私保护模型k-s图,并给出了k-s算法来生成k-s图。理论分析和实验结果表明,k-s算法是正确有效的。更多还原

【Abstract】 Serious concerns on privacy protection in social networks have been raised in recent years.When an adversary uses some types of background knowledge to conduct an attack,an individual’s privacy may be threatened.In pioneer work,node disclosure and edge disclosure were studied.However,there is little effort to deal with sensitivity disclosure.To address it,sensitivity disclosure was formally defined and theoretically analyzed.Taking into account all these disclosures,three level privacy protection was proposed,and k-s graph was presented as the solution.To generate k-s graph,k-salgorithm is both theoretically correct and experimentally effective.更多还原