Sybil-aware least cost rumor blocking in social networks

Rumor blocking and Sybil Attack are regarded as two main security threats in online social networks. The existing work on rumor blocking mainly considers how to minimize the number of protectors used to protect bridge ends. In this study, our experiments based on the Twitter data set show that the existence of the sybil users will dramatically reduce the effectiveness of the rumor blocking by 30%. Motivated by this, we propose a novel sybil-aware least cost rumor blocking framework which jointly considering how to minimize the impact sybil attacks on rumor blocking and optimize the rumor blocking effectiveness. The proposed SLCRB algorithm is well demonstrated by extensive simulations and discussions.