LAŠTOVIČKA, Martin, Tomáš JIRSÍK, Pavel ČELEDA, Stanislav ŠPAČEK and Daniel FILAKOVSKÝ. Passive OS Fingerprinting Methods in the Jungle of Wireless Networks. In NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. Taipei, Taiwan: IEEE Xplore Digital Library. p. nestránkováno, 9 pp. ISBN 978-1-5386-3416-5. doi:10.1109/NOMS.2018.8406262. 2018.
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Basic information
Original name Passive OS Fingerprinting Methods in the Jungle of Wireless Networks
Authors LAŠTOVIČKA, Martin (203 Czech Republic, guarantor, belonging to the institution), Tomáš JIRSÍK (203 Czech Republic, belonging to the institution), Pavel ČELEDA (203 Czech Republic, belonging to the institution), Stanislav ŠPAČEK (203 Czech Republic, belonging to the institution) and Daniel FILAKOVSKÝ (703 Slovakia, belonging to the institution).
Edition Taipei, Taiwan, NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, p. nestránkováno, 9 pp. 2018.
Publisher IEEE Xplore Digital Library
Other information
Original language English
Type of outcome Proceedings paper
Field of Study Informatics
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW URL
RIV identification code RIV/00216224:14610/18:00106883
Organization Ústav výpočetní techniky – Repository – Repository
ISBN 978-1-5386-3416-5
Doi http://dx.doi.org/10.1109/NOMS.2018.8406262
UT WoS 000541820800150
Keywords in English OS fingerprinting;passive monitoring;IPFIX
Links MUNI/A/1213/2017, interní kód Repo. VI20172020070, research and development project.
Changed by Changed by: RNDr. Daniel Jakubík, učo 139797. Changed: 17/5/2022 04:14.
Abstract
Operating system fingerprinting methods are well-known in the domain of static networks and managed environments. Yet few studies tackled this challenge in real networks, where users can bring and connect any device. We evaluate the performance of three OS fingerprinting methods on a large dataset collected from university wireless network. Our results show that method based on HTTP User-agents is the most accurate but can identify only low portion of the traffic. TCP/IP parameters method proved to be the opposite with high identification rate but low accuracy. We also implemented a new method based on detection of communication to OS-specific domains and its performance is comparable to the two established ones. After that, we discuss the impacts of traffic encryption and embracing new protocols such as IPv6 or HTTP/2.0 on OS fingerprinting. Our findings suggest that OS identification based on specific domain detection is viable and corresponds to the current directions of network traffic evolution, while methods based on TCP/IP parameters and User-agents will become ineffective in the future.
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