Abstract:
Systems, methods, and computer program products for passively attributing anonymous network events to their associated users are provided herein. Embodiments include filtering network events over a pre-determined time interval to generate a filtered event list. In an embodiment, event attribution includes attributing an anonymous network event to a user associated with a nearest-neighbor event relative to the anonymous network event. In another embodiment, event attribution includes attributing an anonymous network event to a user associated with an event in the filtered event list, wherein that user maximizes an event attribution function. In a further embodiment, event attribution includes determining a first potential attribution user for an anonymous network event based on a nearest-neighbor attribution approach; determining a second potential attribution user for the anonymous network event based on an event attribution function approach; and comparing the first and second potential attribution users to determine the attribution of the anonymous event.
Abstract:
Systems, methods, and computer program products for passively attributing anonymous network events to their associated users are provided herein. Embodiments include filtering network events over a pre-determined time interval to generate a filtered event list. In an embodiment, event attribution includes attributing an anonymous network event to a user associated with a nearest-neighbor event relative to the anonymous network event. In another embodiment, event attribution includes attributing an anonymous network event to a user associated with an event in the filtered event list, wherein that user maximizes an event attribution function. In a further embodiment, event attribution includes determining a first potential attribution user for an anonymous network event based on a nearest-neighbor attribution approach; determining a second potential attribution user for the anonymous network event based on an event attribution function approach; and comparing the first and second potential attribution users to determine the attribution of the anonymous event.
Abstract:
Methods, systems, and computer program products for insider threat detection are provided. Embodiments detect insiders who act on documents and/or files to which they have access but whose activity is inappropriate or uncharacteristic of them based on their identity, past activity, and/or organizational context. Embodiments work by monitoring the network to detect network activity associated with a set of network protocols; processing the detected activity to generate information-use events; generating contextual information associated with users of the network; and processing the information-use events based on the generated contextual information to generate alerts and threat scores for users of the network. Embodiments provide several information-misuse detectors that are used to examine generated information-use events in view of collected contextual information to detect volumetric anomalies, suspicious and/or evasive behavior. Embodiments provide a user threat ranking system and a user interface to examine user threat scores and analyze user activity.
Abstract:
Methods, systems, and computer program products for insider threat detection are provided. Embodiments detect insiders who act on documents and/or files to which they have access but whose activity is inappropriate or uncharacteristic of them based on their identity, past activity, and/or organizational context. Embodiments work by monitoring the network to detect network activity associated with a set of network protocols; processing the detected activity to generate information-use events; generating contextual information associated with users of the network; and processing the information-use events based on the generated contextual information to generate alerts and threat scores for users of the network. Embodiments provide several information-misuse detectors that are used to examine generated information-use events in view of collected contextual information to detect volumetric anomalies, suspicious and/or evasive behavior. Embodiments provide a user threat ranking system and a user interface to examine user threat scores and analyze user activity.