摘要
为解决直接发布社会网络会侵害个体隐私,进而需要进行隐私保护的问题,针对拥有社会个体邻域信息作为背景知识进行敏感边识别攻击的应用场景,提出了(k,2)-匿名发布的隐私保护方法。该方法通过对原始社会网络图进行最小结构修改,实现最大的数据效用,设计实现了满足隐私保护要求的匿名发布算法,并在数据集上进行了验证。实验结果表明,该方法能有效抵御敏感边的识别攻击,获得可接受的发布质量。
Individual privacy can be breached if social networks are released directly.So privacy protection should be carried on.The privacy protection method named（k,2）-anonymity publication is proposed.The method is suitable for the scene that the aggressor with background knowledge of neighborhood information wants to identify sensitive edges in published social networks.The minimum structural modification is performed on origin social networks graphs and the largest amount of information from the published networks is obtained.Design and implement the algorithm meeting privacy preservation requirements of the published anonymously and carry on experiment on dataset to validate.Experimental results show that the method can effectively resist the sensitive edges identify attack and get acceptable release quality.
出处
《吉林大学学报（信息科学版）》
CAS
2011年第4期324-331,共8页
Journal of Jilin University（Information Science Edition）
基金
国家自然科学基金资助项目(60773049)
江苏大学博士创新计划基金资助项目(CX10B_006X)
吉林省教育厅"十二五"科学技术研究基金资助项目(吉教科合字[2011]第415号)
关键词
社会网络
隐私保护
敏感边
匿名发布
social networks
privacy protection
sensitive edges
anonymous publication
