Concept Stability Based Isolated Maximal Cliques Detection in Dynamic Social Networks.

As the network security gradually deviates from the virtual environment to the real environment, the security problems caused by abnormal users in social networks are becoming increasingly prominent. These abnormal users usually form a group which can be regarded as an isolated network. This paper aims to detect the isolated maximal cliques from a dynamic social network for identifying the abnormal users in order to cut off the source of fake information in time. By virtue of concept stability, an isolated maximal clique detection approach is proposed. Experimental results shown that the proposed algorithm has a high F-measure value for detecting the isolated maximal cliques in social network.