Bans of probability measures in the problem of insider detection

A data model for a common work of a finite set of analysts is considered. Among analysts, there can be an insider who due to access to forbidden data can cause damage to the organization. Operation of each analyst is described by a random series of samples of data, admissible for him. The process of addressing the forbidden data is described by bans of probability measures defining honest operation of analysts. The method of definition of the set of bans which allows to use the theory of bans correctly is constructed. It helps to identify the insider by a finite number of observations over operations of analysts.