Abstract: A system for managing network alerts including data connections adapted to receive alerts from network sensors, alert processing logic coupled to the data connections and further including alert integration logic operable to integrate the alerts, report generation logic coupled to the alert integration logic, distribution logic coupled to the report generation logic and a remote management unit coupled to the alert processing logic and being operable to dynamically modify the alert processing logic.

Abstract: This invention uses Bayesian techniques to prioritize alerts or alert groups generated by intrusion detection systems and other information security devices, such as network analyzers, network monitors, firewalls, antivirus software, authentication services, host and application security services, etc. In a preferred embodiment, alerts are examined for the presence of one or more relevant features, such as the type of an attack, the target of an attack, the outcome of an attack, etc. At least a subset of the features is then provided to a real-time Bayes network, which assigns relevance scores to the received alerts or alert groups. In another embodiment, a network manager (a person) can disagree with the relevance score assigned by the Bayes network, and give an alert or alert group a different relevance score. The Bayes network is then modified so that similar future alerts or alert groups will be assigned a relevance score that more closely matches the score given by the network manager.

Abstract: A method of managing alerts in a network including receiving alerts from network sensors, consolidating the alerts that are indicative of a common incident and generating output reflecting the consolidated alerts.

Abstract: Preferred embodiments combine audit records with other relevant information to identify and track the users, processes or applications responsible for an attack. Information that identifies a user, process, or application may be associated with subsequent audit records related to the user or process session; this information may also be associated with IDS alerts related to the session. By reliably identifying the source of user and process sessions, the preferred embodiments make it possible to selectively target the sessions and applications that are related to an intrusion or attack.

Abstract: This invention uses Bayesian techniques to prioritize alerts or alert groups generated by intrusion detection systems and other information security devices, such as network analyzers, network monitors, firewalls, antivirus software, authentication services, host and application security services, etc. In a preferred embodiment, alerts are examined for the presence of one or more relevant features, such as the type of an attack, the target of an attack, the outcome of an attack, etc. At least a subset of the features is then provided to a real-time Bayes network, which assigns relevance scores to the received alerts or alert groups. In another embodiment, a network manager (a person) can disagree with the relevance score assigned by the Bayes network, and give an alert or alert group a different relevance score. The Bayes network is then modified so that similar future alerts or alert groups will be assigned a relevance score that more closely matches the score given by the network manager.