Social influence aware sybil detection in social networks

Based on the behavior analysis, a Sybil detection mechanism for social networks is proposed in this paper. We calculate the influence of nodes according to static similarity and dynamic similarity, and then identity the suspect nodes. Next, the Hidden Markov Model is adopted to infer the true identity of suspect nodes from their abnormal behaviors, thus the Sybil can be more precisely detected. Results show the proposed mechanism can effectively improve the recognition rate, reduce the false detection rate of the Sybil and protect the privacy and interests of social individuals better.