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A hybrid approach for log signature generation

A hybrid approach for log signature generation 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Computing and Informatics Emerald Publishing

A hybrid approach for log signature generation

A hybrid approach for log signature generation

Applied Computing and Informatics , Volume 19 (1/2): 14 – Jan 12, 2023

Abstract

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.

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Publisher
Emerald Publishing
Copyright
© Prabhat Pokharel, Roshan Pokhrel and Basanta Joshi
ISSN
2634-1964
eISSN
2210-8327
DOI
10.1016/j.aci.2019.05.002
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Applied Computing and InformaticsEmerald Publishing

Published: Jan 12, 2023

Keywords: Log message; Named entity recognition; Density-based spatial clustering; Similarity measure; Support vector machine

References