INTELLIGENCE NETWORK ANOMALY DETECTION USING A TYPE II FUZZY NEURAL NETWORK

摘要

An anomaly detector that implements a type II fuzzy neural network to track symptoms of an attack (which is directed at a private network) and to suggest escalating corrective actions (which can be implemented by a network device) until the symptoms of the attack begin to disappear. A method for addressing a symptom of an attack comprises collecting network statistics; processing each of the collected statistics into a metric which is a fraction of the network statistic divided by a theoretical maximum of the network statistic- calculating averages based on a unique set of the metrics and a rate of change of the unique set; aggregating a unique set of the calculated averages and comparing the aggregated averages to threshold values in an if-then-else decision rules table to determine an action to address the symptom of the attack.