基于邻居度序列相似度的k-度匿名隐私保护方案  

K-degree anonymity scheme for preserving privacy based on similarity of neighborhood degree sequence

作　　者：周克涛 刘卫国[1] 施荣华[1] ZHOU Ketao;LIU Weiguo;SHI Ronghua(School of Information Science and Engineering, Central South University, Changsha 410083, China)

机构地区：[1]中南大学信息科学与工程学院,长沙410083

出　　处：《计算机工程与应用》2017年第19期102-108,共7页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61073187)

摘　　要：针对传统的k-度匿名方案添加随机噪声次数过多,构图成功率低,且无法抵御更复杂的图查询背景知识攻击的问题,提出了改进的k-度匿名隐私保护方案。该方案提出一种优先级构图算法,通过设置参数来调整邻居节点与度需求高的节点之间的权重,引入欧式距离并对k-度匿名后的同度节点构造出相似度较高的邻居度序列。实验结果表明,该方案的度信息损失较少,能够调节边信息损失与构图成功率之间的冲突,抵御以节点的度结合邻居度序列作为背景知识的攻击。Aiming at the problem of traditional k-degree methods which usually add a huge amount of random noise,have low success rate in re-constructing graph and cannot resist attacks based on more complex background knowledge ofgraph query,an advanced k-degree scheme is presented for preserving privacy.The scheme brings up the priority algorithmfor constructing graph,adjusts the weights between neighborhood of nodes and the highest demand node by settingsome parameters and introduces Euclidean distance to construct similar neighborhood degree sequence of nodes with thesame degree after anonymity.Experimental results show that this scheme has less degree loss and can regulate collisionbetween information loss and success rate of constructing graph,resist attacks about combining background knowledge ofdegree of nodes and their neighborhood degree sequence.

关 键 词：社交网络 隐私保护 k-度匿名 优先级算法 邻居度序列 欧式距离 

分 类 号：TP309.2[自动化与计算机技术—计算机系统结构]