DeepSyslog: Deep Anomaly Detection on Syslog Using Sentence Embedding and Metadata
Published in IEEE Transactions on Information Forensics and Security, 2022
In this paper, we propose DeepSyslog, a deep anomaly detection method for Syslog that integrates unsupervised sentence embedding with event metadata to capture contextual semantics and improve detection accuracy, outperforming existing log-based approaches.
Recommended citation: J. Zhou, Y. Qian, Q. Zou, P. Liu and J. Xiang, "DeepSyslog: Deep Anomaly Detection on Syslog Using Sentence Embedding and Metadata," in IEEE Transactions on Information Forensics and Security, vol. 17, pp. 3051-3061, 2022, doi: 10.1109/TIFS.2022.3201379. keywords: {Metadata;Anomaly detection;Feature extraction;Semantics;Indexes;History;Event detection;Anomaly detection;sentence embedding;event metadata}, https://ieeexplore.ieee.org/document/9865986