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Fingerprinting encrypted network traffic types using machine learning

Sam Leroux (UGent) , Steven Bohez (UGent) , Pieter-Jan Maenhaut (UGent) , Nathan Meheus, Pieter Simoens (UGent) and Bart Dhoedt (UGent)
(2018) p.1-5
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Citation

Please use this url to cite or link to this publication:

Chicago
Leroux, Sam, Steven Bohez, Pieter-Jan Maenhaut, Nathan Meheus, Pieter Simoens, and Bart Dhoedt. 2018. “Fingerprinting Encrypted Network Traffic Types Using Machine Learning.” In , 1–5.
APA
Leroux, S., Bohez, S., Maenhaut, P.-J., Meheus, N., Simoens, P., & Dhoedt, B. (2018). Fingerprinting encrypted network traffic types using machine learning (pp. 1–5). Presented at the NOMS2018, the IEEE/IFIP Network Operations and Management Symposium .
Vancouver
1.
Leroux S, Bohez S, Maenhaut P-J, Meheus N, Simoens P, Dhoedt B. Fingerprinting encrypted network traffic types using machine learning. 2018. p. 1–5.
MLA
Leroux, Sam, Steven Bohez, Pieter-Jan Maenhaut, et al. “Fingerprinting Encrypted Network Traffic Types Using Machine Learning.” 2018. 1–5. Print.
@inproceedings{8559975,
  author       = {Leroux, Sam and Bohez, Steven and Maenhaut, Pieter-Jan and Meheus, Nathan and Simoens, Pieter and Dhoedt, Bart},
  isbn         = {978-1-5386-3416-5},
  language     = {eng},
  location     = {Taipei, Taiwan},
  pages        = {1--5},
  title        = {Fingerprinting encrypted network traffic types using machine learning},
  year         = {2018},
}