As traditional privacy-preserving technology cant be directly applied to the social network data of higher dimension

to solve published graph data for social network facing the issues of privacy disclosure

a -isomorphism privacy protection algorithm is proposed.By the original graph data is divided into sub-graphs effectively

in order to reduce the cost of anonymity

the number of edges added edges approximately equal to the deleted

and ensure the release of the graph data is the isomorphic

which effectively prevents the attacker based on a structural background knowledge attack.Real data set by experiment results show that the algorithm has high validity and can reduce the loss of information

also improve the quality of anonymity.