A tool to generate causal DAGs from syslog time-series.
Project description
Overview
This package generates causal DAGs among time-series events in syslog data. This package works on python3. The input log data is loaded with AMULOG (https://github.com/cpflat/amulog). The output DAG is recorded in the format of NetworkX DiGraph.
This project was partially forked from repository LogCausalAnaysis. (https://github.com/cpflat/LogCausalAnalysis)
Usage
All features are available from command line. First you should try following help command python -m logdag -h
.
short usage:
Generate amulog database (and its config) as the input log time-series source
Prepare logdag config file by referring
logdag/data/config.conf.default
Generate time-series db by
logdag.source
featuresGenerate DAGs by subcommand
makedag
See results by commands such as
show-edge-list
Reference
This project is evaluated in some papers CNSM2019 and TNSM2018. If you use this code, please consider citing:
@inproceedings{Kobayashi_CNSM2019, author = {Kobayashi, Satoru and Otomo, Kazuki and Fukuda, Kensuke}, booktitle = {Proceedings of the 15th International Conference on Network and Service Management (CNSM'20)}, title = {Causal analysis of network logs with layered protocols and topology knowledge}, pages = {1-9}, year = {2019} } @article{Kobayashi_TNSM2018, author = {Kobayashi, Satoru and Otomo, Kazuki and Fukuda, Kensuke and Esaki, Hiroshi}, journal = {IEEE Transactions on Network and Service Management}, volume = {15}, number = {1}, pages = {53-67}, title = {Mining causes of network events in log data with causal inference}, year = {2018} }
License
3-Clause BSD license
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