Abstract: Disclosed are methods for automatic categorization of internal and external communication, the method including the steps of: defining groups of entities that transmit data; monitoring data flow of the groups; extracting the data, from the data flow, for learning traffic-flow characteristics of the groups; classifying the data into group flows; upon the data being transmitted, checking the data to determine whether the data is designated as group-internal; and blocking data traffic for data that is group-internal. Preferably, the step of monitoring includes assigning data weights to the data using Bayesian methods. Most preferably, the step of classifying includes classifying the data using Bayesian methods for evaluating the data weights. Preferably, the step of blocking includes blocking data traffic between members of two or more groups. Preferably, the method further includes the step of: enabling an authorized entity to unblock the data traffic.

Abstract: Disclosed are methods for automatic categorization of internal and external communication, the method including the steps of: defining groups of entities that transmit data; monitoring data flow of the groups; extracting the data, from the data flow, for learning traffic-flow characteristics of the groups; classifying the data into group flows; upon the data being transmitted, checking the data to determine whether the data is designated as group-internal; and blocking data traffic for data that is group-internal. Preferably, the step of monitoring includes assigning data weights to the data using Bayesian methods. Most preferably, the step of classifying includes classifying the data using Bayesian methods for evaluating the data weights. Preferably, the step of blocking includes blocking data traffic between members of two or more groups. Preferably, the method further includes the step of: enabling an authorized entity to unblock the data traffic.