A hybrid approach for log signature generation
Гибридный подход к генерации сигнатур журналов
2019-05-14
SCID: 54.1/fvq78bjg
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Named Entity Recognitionevent log analysislog pattern clusteringlog signature extractionvariable entity extraction
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Abstract (AI)
Analysis of log message is very important for the identification of a suspicious system and network activity. This analysis requires the correct extraction of variable entities. The variable entities are extracted by comparing the logs messages against the log patterns. Each of these log patterns can be represented in the form of a log signature. In this paper, we present a hybrid approach for log signature extraction. The approach consists of two modules. The first module identifies log patterns by generating log clusters. The second module uses Named Entity Recognition (NER) to extract signatures by using the extracted log clusters. Experiments were performed on event logs from Windows Operating System, Exchange and Unix and validation of the result was done by comparing the signatures and the variable entities against the standard log documentation. The outcome of the experiments was that extracted signatures were ready to be used with a high degree of accuracy.
Key Findings
1
Extracted signatures were reported as ready for use with a high degree of accuracy.
2
The approach was evaluated on Windows, Exchange, and Unix event logs against standard log documentation.
3
The first module identifies log patterns by grouping messages into log clusters.
4
The paper introduces a hybrid log-signature extraction approach combining log clustering with Named Entity Recognition (NER).
5
The second module extracts log signatures and variable entities using NER applied to the identified log clusters.
Research Object
system and network event logs from Windows, Exchange, and Unix
Research Subject
accurate log signature generation through log-pattern clustering and Named Entity Recognition-based extraction of variable entities
Publication Details
Publication Date
2019-05-14
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