Device and network classification based on probabilistic model
Abstract:
Programmatic mechanisms that enable the automatic assignment of categories to network entities based on observed evidence. Agents gather observation data that identifies observations made by agents about the network and a plurality of nodes of the network. The agents provide the observation data to a classification module, which assigns a device category to the nodes of the network based on the observation data and a probabilistic node model. The probabilistic node model considers several probabilities to ascertain a recommended device category for a particular node, such as probabilities based on a manufacturer of a node, an operating system executing on a node, information about other nodes in the local vicinity of a node, and an administrator web page associated with a node. The classification module may also assign a particular network category to the network based on the observation data and a probabilistic network model.
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