Publication

Abstract : The arrival of social network sites in the last years seems to be a trend that will likely continue. What naive technology users may not realize is that the information they provide online is stored and may be used for various purposes. The social network datasets are used by researchers from many disciplines. Anonymization of the data can mitigate this privacy and security concerns. Anonymization is intended to exactly preserve the pure structure of the graph while suppressing the who information. Usually attributes that needs to be anonymized are taking randomly and after measuring information loss identifies the optimal attributes. But here the concept of most influential nodes is used to identify strong attributes which can be anonymized to obtain better privacy. Here in this project by identifying most influential nodes in the social network and their strong attributes anonymization can be performed with less information loss.