Abstract: A method of identifying anomalous network activity. The method includes identifying, based on network data representative of network activity within a network, at least one instance of a sequence of events that occurred within the network. A probability of the sequence of events occurring during non-anomalous network activity is obtained based on transition probabilities between events in the sequence of events. A frequency characteristic dependent on a frequency at which the sequence of events occurred within the network is determined. A likelihood of the sequence of events occurring within the network at the frequency is determined based on a combination of the probability and the frequency characteristic. It is identified, based on the likelihood, that at least a portion of the network data is anomalous.

Abstract: A method of identifying anomalous data obtained by at least one sensor of a plurality of sensors located within an environment. The method includes identifying, based on sensor data obtained from the plurality of sensors, at least one instance of a sequence of events that occurred within the environment. A probability of the sequence of events occurring within the environment under non-anomalous conditions is obtained. A frequency characteristic dependent on a frequency at which the sequence of events occurred within the environment is determined. A likelihood of the sequence of events occurring within the environment at the frequency is determined, based on a combination of the probability and the frequency characteristic. It is identified, based on the likelihood, that at least a portion of the sensor data is anomalous.