nLSALog: An Anomaly Detection Framework for Log Sequence in Security Management

nLSALog: An Anomaly Detection Framework for Log Sequence in Security Management

For the security defense in the current Intelligent Transportation System (ITS), malware is often used as the security analysis data source, but only the known attack type can be detected. A general anomaly detection framework is proposed, using log data as the analysis data source. By modeling the...

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Bibliographic Details
Main Authors: Ruipeng Yang, Dan Qu, Ying Gao, Yekui Qian, Yongwang Tang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Log sequence anomaly detection
intelligent transportation system
self attention
word embedding
LSTM
Online Access:https://ieeexplore.ieee.org/document/8903291/

Internet

https://ieeexplore.ieee.org/document/8903291/

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