  Intrusion detection systems (IDSs) have become a widely used measure for
security systems. The main problem for those systems results is the irrelevant
alerts on those results. We will propose a data mining based method for
classification to distinguish serious alerts and irrelevant one with a
performance of 99.9% which is better in comparison with the other recent data
mining methods that have reached the performance of 97%. A ranked alerts list
also created according to alerts importance to minimize human interventions.
