1. A similarity detection system receiving a plurality of input entities, the system comprising: a face detection and verification device configured to extract a face region from the plurality of input entities and to extract shift features from the face region as images, the face detection and verification device excludes items in the input entities that have facial features but are not a real face of a person; a multi-scale SIFT and spatial histograms device configured to transform the images into vectors including attributes of the plurality of input entities such that a distance between points on the images is detected to calculate a similarity between the images; a cohesive subgraph identification device configured to calculate, based on the attributes of the plurality of input entities, a first parameter and a second parameter based on the first parameter, and further configured to identify a plurality of subgraphs from the second parameter; and a subgraph correlation tracking and clustering device configured to determine a relationship between different subgraphs based on a similarity factor between the second parameter and the plurality of subgraphs, wherein the first parameter includes k-cores and the second parameter includes (k, d)-cores, wherein the subgraph correlation tracking and clustering device is further configured to output outliers that include the subgraphs not combined by the subgraph correlation tracking and clustering device, wherein the subgraph correlation tracking and clustering device is further configured to divide the different subgraphs into a plurality of groups of subgraphs based on the similarity factor between the second parameter and the plurality of subgraphs, wherein the subgraph correlation tracking and clustering device uses source nodes and target nodes of nodes in a post network such that on each iteration, each source node propagates its edge similarities to its neighborhood along paths, and meanwhile, each target node aggregates the similarities that are propagated in from their neighbors, wherein given a maximal path length, path similarities aggregated by each target node are computed by multiplying all edge similarities along the path, and wherein the subgraph correlation tracking and clustering device measures the correlations between subgraphs to detect outliers within the images and based on the correlation between the subgraphs and similarities, the subgraph correlation tracking and clustering device combines subgraphs to output inliers.