Discovery of Network Information Content Security Incidents Based on CCGA

This paper aims at the discovery of network Information Content Security Incidents (ICSI) in the field of information security. It analysis the features of ICSI and using the character of relationship between communication data sets and item sets which needed to discover the incidents, and it transforms the discovery of ICSI into association rules in data sets. It proposes an algorithm based on cooperation co-evolution genetic which uses genetic algorithm for each sub-species population formed by item sets to evolution as a local solution. And it uses co-evolution to evolve in dominant population and to achieve information’s interaction and transmission which will integrate local solutions to obtain global solution. Simulation results show that the algorithm is feasible and effective. It has more advantages than classic Apriori algorithm.