The development of several popular social networks in recent days and publication of social network data has led to the danger of disclosure of sensitive information of individuals. This necessitated the preservation of privacy before the publication of such data. There are several algorithms developed to preserve privacy in micro data. But these algorithms cannot be applied directly as in social networks the nodes have structural properties along with their labels. k-anonymity and l-diversity are efficient tools to anonymise micro data. So efforts have been made to find out similar algorithms to handle social network anonymisation. In this paper we propose an algorithm which can be used to achieve k-anonymity and l-diversity in social network anonymisation. This algorithm is based upon some existing algorithms developed in this direction. © 2012 IEEE.