An Anomaly Detection Method Based on Adaptive Log and Dual Feature Fusion Analysis for Distributed Systems
Yijiang Jia, Kefei Li, Ping C. Lu, Baodi Xie, Huayang Wang, Jincai Chen · 2023
In this study, we present a middleware-based approach for detecting anomalies in distributed systems. Our method facilitates the dynamic collection of logs at various levels of detail and incorporates an a priori dictionary-based compression strategy to process and transmit logs, minimizing the performance impact on distributed systems. Additionally, we utilize a dual feature fusion technique to analyze the logs. We evaluate the effectiveness of our approach by performing anomaly detection in a publish/subscribe distributed system and comparing it with existing methods. The results illustrate that our method outperforms other approaches, demonstrating superior performance.