Intrusion Detection using Genetically Generated Finite Automata

Two new methods for detecting network attacks using genetically generated finite automata with a) the transitions actions, and b) with the selected states are presented. The first method is based on the “flib” model that can predict changes in network activity on the basis of progressived analysis of network records in the KDD-99 format. The second method is an adaptation of a classical finite automata.

finite automata, network attack, genetic algorithm, mutation, crossover, recall, precision, “flib”, state