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@inproceedings{1196642,
author = {Jirsík, Tomáš and Čeleda, Pavel},
address = {Heidelberg},
booktitle = {Advances in Communication Networking, Lecture Notes in Computer Science, Vol. 8846},
doi = {http://dx.doi.org/10.1007/978-3-319-13488-8_7},
editor = {Yvon Kermarrec},
keywords = {OS fingerprinting; passive; high-throughput; p0f; flow},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Heidelberg},
isbn = {978-3-319-13487-1},
pages = {70-73},
publisher = {Springer International Publishing},
title = {Identifying Operating System Using Flow-based Traffic Fingerprinting},
url = {http://dx.doi.org/10.1007/978-3-319-13488-8_7},
year = {2014}
}
TY - JOUR
ID - 1196642
AU - Jirsík, Tomáš - Čeleda, Pavel
PY - 2014
TI - Identifying Operating System Using Flow-based Traffic Fingerprinting
PB - Springer International Publishing
CY - Heidelberg
SN - 9783319134871
KW - OS fingerprinting
KW - passive
KW - high-throughput
KW - p0f
KW - flow
UR - http://dx.doi.org/10.1007/978-3-319-13488-8_7
N2 - Many vulnerabilities are operating system specific. Information about the OS of all hosts in a network represents a valuable asset for network administrators. While OS detection in small networks is an easy task, expanding the same process on a large scale becomes a challenge. The weak performance, high speed traffic and large amount of hosts for OS detection are issues to overcome. In this paper we propose a flow based framework for large scale OS detection. Furthermore, we describe the framework implementation into a flow probe, provide performance comparison and share remarks on deployment in a real world network.
ER -
JIRSÍK, Tomáš a Pavel ČELEDA. Identifying Operating System Using Flow-based Traffic Fingerprinting. In Yvon Kermarrec. \textit{Advances in Communication Networking, Lecture Notes in Computer Science, Vol. 8846}. Heidelberg: Springer International Publishing, 2014, s.~70-73. ISBN~978-3-319-13487-1. Dostupné z: https://dx.doi.org/10.1007/978-3-319-13488-8\_{}7.
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