On the Infeasibility of Modeling Polymorphic Shellcode - Re-Thinking the Role of Learning in Intrusion Detection Systems

Cite

Text

Song et al. "On the Infeasibility of Modeling Polymorphic Shellcode - Re-Thinking the Role of Learning in Intrusion Detection Systems." Machine Learning, 2010. doi:10.1007/S10994-009-5143-5

Markdown

[Song et al. "On the Infeasibility of Modeling Polymorphic Shellcode - Re-Thinking the Role of Learning in Intrusion Detection Systems." Machine Learning, 2010.](https://mlanthology.org/mlj/2010/song2010mlj-infeasibility/) doi:10.1007/S10994-009-5143-5

BibTeX

@article{song2010mlj-infeasibility,
  title     = {{On the Infeasibility of Modeling Polymorphic Shellcode - Re-Thinking the Role of Learning in Intrusion Detection Systems}},
  author    = {Song, Yingbo and Locasto, Michael E. and Stavrou, Angelos and Keromytis, Angelos D. and Stolfo, Salvatore J.},
  journal   = {Machine Learning},
  year      = {2010},
  pages     = {179-205},
  doi       = {10.1007/S10994-009-5143-5},
  volume    = {81},
  url       = {https://mlanthology.org/mlj/2010/song2010mlj-infeasibility/}
}