This paper introduces an intrusion detection method based on information feedback to overcome the problem of high false alarm rate,especially for unknown abnormal data.

The producing reason of false alarm rate and missed alarm rate,along with their correlation in radiation dosimetry are discussed from the point of view of statistics in this article.

The solution to the false alarm rate and a higher rate of Omission of the computer alarm system is suggested.

Reduction on false positive rate of anomaly IDS

Scoring the true positive rate and the false positive rate is a key component in IDS evaluation.

It is an important research topic to improve detection rate and reduce false positive rate of the detection model in the field of intrusion detection.

After testing common network software,experimental result shows that compared with single source code analysis,this technology can reduce false positives and false negatives effectivel.

To cope with the problem of high false positives and false negatives in source code static analysis methods,this paper presents a source code static analysis technology for vulnerability detection based on data fusion.

Some research has been done like analysis of detection sensitivity,setting of threshold,division of alarm grade,analysis of false alarm probability,etc.

The results show that we can trade off among false negative,false positive and error rate of rare class by changing cost matrix,which can mi.

But the relationships among security events are often ignored by the current intrusion detection systems(IDS),and an important problem in the field of IDS is a large volume of false positive which tends to overwhelm human operators.

Gave the test of the Trojan detection based on the artificial immune principle to prove that this Trojan detection system can improve the detection rate and reduce the rate of false alarm.