Abstract：Existing studies have shown that the weigh between privacy and utility upon anonymous social network publishing data becomes an important and challenging issue，while users′ sensitive attributes are important privacy information.In order to efficiently solve the sensitive attributes leaking problem in social network，we propose a personalized protection algorithm based utility PKDU model.First，calculate the sensitivity of the user attributes，the protection objects change from a sensitive attribute to specific attribute values；then，partition or consolidate the noncritical nodes containing sensitive attribute value，and generalize attributes of the key nodes.Experimental results show that，compared to Kdegree algorithm，PKDU algorithm can guarantee higher data availability，while effectively against private information disclosure.
谢玉芹,郑明春. 一种个性化的社交用户信息隐私保护算法[J]. 小型微型计算机系统, 2017, 38(7): 1490-1494.
XIE Yu-qin,ZHENG Ming-chun. Personalized Social Network User Information Privacy Preserving Algorithm. Journal of Chinese Computer Systems, 2017, 38(7): 1490-1494.
2017, Vol. 38 
