Implementation of an Integrated Log Analysis System Through Statistics-Based Prediction Techniques

Abstract

Integrated log analysis systems, which could collect, store and analyze a large volume of log and big data in real time by analyzing firewall logs, continue to expand their applications to a variety of fields such as abnormal network behavior detection, use pattern analysis with web log analysis, fraudulent order analysis and detection for internet shopping malls, inside information leakage analysis and detection. This paper presents a result of designing and implementing an prediction engine applying statistics-based log analysis(regression analysis, time-series analysis, cluster analysis and discriminant analysis etc.) technologies, which could overcome problems of trying to implement with GNUR, mathematical and statistical libraries, for finding preemptive action through concentrated guard during an expected security accident time period by analyzing and predicting security-related infra logs.