A method of multi-IDS cooperation to improve detection creditability is presented after analyzing false negative rate and false positive rate of IDS and the result fusion is based on boosting Bayesian classification algorithm.
False positive rate and false negative rate affected the detection creditability of intrusion detection systems(IDS).This paper presented a method of multi-IDS cooperation to improve detection creditability after analyzing false negative rate and false positive rate of IDS.The result fusion based on boosting Bayesian classification algorithm,which put different weights on single IDS and sum the result,then choose the greatest one.The experiments show that the method can reduce the false positive rate and false negative rate,and then improve the detection creditability.