Nowadays most prior privacy protection techniques focus on static social networks. However, there are additional privacy disclosures in dynamic social networks due to the sequential publications. To protect against such an adversary, a new dynamic privacy scheme was introduced, named kw-SDA(dynamic kwstructural diversity anonymity).Which ensured that the probability of a vertex/ community identity being revealed in sequential releases was limited to 1/k by protecting individuals in groups. After that, a scalable heuristic algorithm was develaped to provide dynamic kw-SDA. The proposed algorithm anonymize the graph based on the previous w-1 releases and minimize the graph alterations. Moreover, by introducing a table, named CS-Table, the algorithm incrementally summarized the vertex information in sequential releases, and avoided the need of scanning all the releases for anonymization. The evaluations show that the approach retain much of the characteristics of the networks while confirming the privacy protection.