Communication network anomaly detection based on log file analysis

Abstract

Communication network today are becoming larger and increasingly complex. Failure in communication systems will cause loss of critical data and even economic losses. Therefore, detecting failures and diagnosing their rootcause in a timely manner is essential. Fast and accurate detection of these failures can accelerate problem determination, and thereby improve system reliability. Today log files have been paid attention on system and network failure detection, but it is still a challenging task to build an efficient model to detect anomaly from log files. To this effect, we propose a novel approach, which aims to detect frequent patterns from log files to build the normal profile, and then to identify the anomalous behaviour in log files. The experimental results demonstrate that our approach is an efficient way for anomaly detection with high accuracy and few false positives.