| 摘要 |
An anomaly detection method, for detecting anomalous behavior associated with a particular element of a domain of interest with which domain human beings interact, comprises: constructing in respect of a set of entities, comprising human beings and/or human institutions which are associated or potentially associated with the domain, a network representing inter-entity and intra-entity connections; performing statistical analysis of a population, including the human beings or human institutions in the set of entities, on the basis of known behavioral characteristic data, to determine a typical behaviour pattern for the population in respect of the particular element on which the anomaly detection method is focused; extracting from the constructed connection network an ego-centric sub-network (social network) of entities associated with the focal element; correlating an actual behavior pattern of the entities in the sub-network with the determined typical behaviour pattern to find behavioral abnormalities in the actual behaviour pattern. The method further comprises providing an output identifying one or more abnormalities in the actual behavior pattern of the entities in the sub-network found from such correlation. In particular the method is applied to detecting anomalous behavior in stocks and trading networks. |
