LogGAN: a Log-level Generative Adversarial Network for Anomaly Detection using Permutation Event Modeling

Bin Xia 0003, Yuxuan Bai, Junjie Yin, Yun Li 0009, Jian Xu 0009. LogGAN: a Log-level Generative Adversarial Network for Anomaly Detection using Permutation Event Modeling. Information Systems Frontiers, 23(2):285-298, 2021. [doi]

@article{XiaBYLX21,
  title = {LogGAN: a Log-level Generative Adversarial Network for Anomaly Detection using Permutation Event Modeling},
  author = {Bin Xia 0003 and Yuxuan Bai and Junjie Yin and Yun Li 0009 and Jian Xu 0009},
  year = {2021},
  doi = {10.1007/s10796-020-10026-3},
  url = {https://doi.org/10.1007/s10796-020-10026-3},
  researchr = {https://researchr.org/publication/XiaBYLX21},
  cites = {0},
  citedby = {0},
  journal = {Information Systems Frontiers},
  volume = {23},
  number = {2},
  pages = {285-298},
}