A model for website anomaly detection based on log analysis

To found security events from web logs has become an important aspect of network security. This paper proposes a website anomaly detection model based on security-log-analysis. After creating a anomaly feature sets of the model, C4.5 algorithm was used to improve feature sets, making the abnormal records in feature sets store hierarchically. Compared logs in website with the treated feature stes, the model ultimately achieves the purpose of checking website´s security event fast and accurately.