Abstract: A method of network surveillance includes receiving network packets handled by a network entity and building at least one long-term and at least one short-term statistical profile from a measure of the network packets that monitors data transfers, errors, or network connections. A comparison of the statistical profiles is used to determine whether the difference between the statistical profiles indicates suspicious network activity.

Abstract: A method of network surveillance includes receiving network packets handled by a network entity and building at least one long-term and at least one short-term statistical profile from a measure of the network packets that monitors data transfers, errors, or network connections. A comparison of the statistical profiles is used to determine whether the difference between the statistical profiles indicates suspicious network activity.

Abstract: This invention uses probabilistic correlation techniques to increase sensitivity, reduce false alarms, and improve alert report quality in intrusion detection systems. In one preferred embodiment, an intrusion detection system includes at least two sensors to monitor different aspects of a computer network, such as a sensor that monitors network traffic and a sensor that discovers and monitors available network resources. The sensors are correlated in that the belief state of one sensor is used to update or modify the belief state of another sensor. In another embodiment of this invention, probabilistic correlation techniques are used to organize alerts generated by different sensors in an intrusion detection system.

Abstract: A method of network surveillance includes receiving network packets handled by a network entity and building at least one long-term and at least one short-term statistical profile from a measure of the network packets that monitors data transfers, errors, or network connections. A comparison of the statistical profiles is used to determine whether the difference between the statistical profiles indicates suspicious network activity.

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: 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: This invention uses probabilistic correlation techniques to increase sensitivity, reduce false alarms, and improve alert report quality in intrusion detection systems. In one preferred embodiment, an intrusion detection system includes at least two sensors to monitor different aspects of a computer network, such as a sensor that monitors network traffic and a sensor that discovers and monitors available network resources. The sensors are correlated in that the belief state of one sensor is used to update or modify the belief state of another sensor. In another embodiment of this invention, probabilistic correlation techniques are used to organize alerts generated by different sensors in an intrusion detection system.