Incognizance of Social Networks by Sequential Clustering

The complexity in preserving privacy of social networks is considered. The distributed setting in which the network data is split between several data holders is focussed. The goal is to arrive at an anonymized view of the unified network in a distributed environment. The leading clustering algorithm for achieving anonymity is SANGreeA (Social Network Greedy Anonymization), which is significantly outperformed by our proposed clustering algorithmic techniques. To the best of our knowledge, this is the first study for privacy preservation in distributed social network.