Alarm Correlation Analysis Method Based on Fuzzy Immune Evolution

Abstract

This paper proposes a correlation analysis method based on fuzzy rules and artificial immune. Firstly, we adopt the alarms selection algorithm based on a sliding time window to improve the efficiency of selected alarm. Secondly, the analysis method based on fuzzy correlation rules is used to associate the known patterns static and rapidly. Then, using a method based on immune evolution to improve and adaptive the antibody so as to achieve the dynamic, intelligent correlation of unknown model. The experimental results in LLDOS1.0 and LLDOS2.0 show that the new method gets better accuracy than typical correlation methods, which can ensure the efficiency of correlation analysis and the adaptability of the correlation method.