摘要
提出了一种针对有向社交网络的Sybil检测方法——SybilGrid法.该方法采用针对有向社交网络拓扑的随机游走策略来检测Sybil节点.通过采集新浪微博上的真实社交网络拓扑数据,对算法的性能进行了评估,证明了算法的有效性.与现有的SybilDefender方法进行了对比分析,对于同样数量的攻击边,SybilDefender法的虚警率为SybilGrid法的1.6倍左右;同时,为了达到相同的虚警率,SybilGrid法所需要的游走路径长度更短,即SybilGrid法的检测效率更高.
A Sybil detection method based on the random walk strategy is proposed to detect the Sybil nodes in the directed social network.The performance of the algorithm is evaluated by collecting the real social network topological data on Sina Weibo,and the effectiveness of the algorithm is proved.In addition,compared with the existing SybilDefender method,it is found that the false alarm rate of SybilDefender is about 1.6times as great as SybilGrid.Meanwhile,to achive the same false alarm probability,the random walk length required by SybilGrid is much shorter,meaning that the detection efficiency of SybilGrid is higher.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2016年第2期199-204,共6页
Journal of Xidian University
基金
国家自然科学基金资助项目(61372076
61301171)
高等学校学科创新引智计划资助项目(B08038)
中央高校基本科研业务费专项资金资助项目(K5051301059
K5051201021)
