Abstract: Because of scientific researching and data sharing, social networks data should be released. However, individual privacy will be breached if social networks data will be published directly. Therefore, privacy protection should be carried on while releasing social networks data. A privacy protection method based on k-anonymity was proposed. The method is suitable for the scene that the aggressor with background knowledge of neighborhood information wants to reidentify the target node in published social networks. According to the individual privacy protection rectuirement, the entities set different levels of privacy protection to share data and improve data utility as possible as. Designed and implemented the KNP algorithm to publish data anonymously and carry on experiment on dataset to validate the algorithm. Experimental results show that the algorithm can effectively resist the neighborhood attack.

Key words: Social networks, Privacy protection,k-anonymity, Neighborhood attack