Anomaly Detection in Cybersecurity Events Through Graph Neural Network and Transformer Based Model: A Case Study with BETH Dataset. Lakha, B., Mount, S. L., Serra, E., & Cuzzocrea, A. In IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan, December 17-20, 2022, pages 5756–5764, 2022.
Anomaly Detection in Cybersecurity Events Through Graph Neural Network and Transformer Based Model: A Case Study with BETH Dataset [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/bigdataconf/LakhaMSC22,
  author       = {Bishal Lakha and
                  Sara Lilly Mount and
                  Edoardo Serra and
                  Alfredo Cuzzocrea},
  title        = {Anomaly Detection in Cybersecurity Events Through Graph Neural Network
                  and Transformer Based Model: {A} Case Study with {BETH} Dataset},
  booktitle    = {{IEEE} International Conference on Big Data, Big Data 2022, Osaka,
                  Japan, December 17-20, 2022},
  pages        = {5756--5764},
  year         = {2022},
  crossref     = {DBLP:conf/bigdataconf/2022},
  url          = {https://doi.org/10.1109/BigData55660.2022.10020336},
  doi          = {10.1109/BIGDATA55660.2022.10020336},
  timestamp    = {Fri, 18 Aug 2023 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/bigdataconf/LakhaMSC22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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