Abstract: A method for detecting nodes in an enterprise network infected with aberrant code is presented in which traffic conversation information representative of traffic conversation in the enterprise network over an analysis period is obtained. Analysis of the obtained traffic conversation information identifies suspected infected nodes in the enterprise network that exhibit behavior outside of the normal behavior associated with the one or more traffic conversation factors. Anomaly analysis may be performed on traffic conversation information associated with the suspected infected nodes to identify any existing infected nodes in the enterprise network.

Abstract: A system and method for automatically constructing a baseline for an attribute of a monitored system, calculating a threshold based on the constructed baseline, and feeding the threshold back into the monitored system is presented. In accordance with the invention, a metric corresponding to an attribute of interest of a monitored system is extracted and compared with a current normal threshold associated with the attribute. An event notification is generated if the extracted metric is not within a limit defined by the current normal threshold. A baseline is calculated based on a relevant subset of extracted metrics, from which a new current normal threshold is calculated. The current normal threshold is reconfigured with the new current normal threshold. In preferred embodiments, an alarm is generated if one or more event notifications meet the conditions of pre-specified rules.