SSADlog pre-processed BGL dataset
- Citation Author(s):
-
Zhisheng Zhou
- Submitted by:
- meixiu zhou
- Last updated:
- DOI:
- 10.21227/jp09-rs47
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- Categories:
- Keywords:
Abstract
SSADLog is a novel log-based anomaly detection framework. It introduces a hyper-efficient log data pre-processing method that generates a representative subset of small sample logs. This is SSADLog pre-processed BGL dataset which are used in training, test1 and test2. You can see the small sample datasets significantly reduce the time required to execute the entire SSADLog framework but still provide a holistic understanding of the original log sequences.
SSADLog is a novel log-based anomaly detection framework. It introduces a hyper-efficient log data pre-processing method that generates a representative subset of small sample logs. This is SSADLog pre-processed BGL dataset which are used in training, test1 and test2. You can see the small sample datasets significantly reduce the time required to execute the entire SSADLog framework but still provide a holistic understanding of the original log sequences.
Instructions:
Please refer to https://github.com/NickZhouSZ/SSADLog for the code and guideline
on how to use the dataset.
