FastLogAD

Official Implementation of "FastLogAD: Log Anomaly Detection with Mask-Guided Pseudo Anomaly Generation and Discrimination" read here

Install Requirements

pip install -r requirements.txt

Process Data

1. Download and extract HDFS dataset from here
2. Before processing data, set the following directories for each corresponding dataset.py under dataprocess directory:

   input_dir =   # i.e. .../BGL/
   output_dir = # i.e. .../BGL/output/
   

3. Run parsing and processing(into sequences):

   python -m dataprocess.[dataset name]
   

   [dataset name]: hdfs, bgl, thunderbird

Run FastLogAD

1. Set the proper directories and hyperparameters in each .yaml file under configs

2. Run the main module with your choice of the generator variant(MLM, Random)

   i.e. MLM generator variant on HDFS:

   python -m main --config hdfs.yaml
   

   Random generator variant on Thunderbird:

   python -m main --config thunderbird.yaml