Using TLS Fingerprints for OS Identification in Encrypted Traffic
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F20%3A00115200" target="_blank" >RIV/00216224:14610/20:00115200 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/NOMS47738.2020.9110319" target="_blank" >http://dx.doi.org/10.1109/NOMS47738.2020.9110319</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/NOMS47738.2020.9110319" target="_blank" >10.1109/NOMS47738.2020.9110319</a>
Alternative languages
Result language
angličtina
Original language name
Using TLS Fingerprints for OS Identification in Encrypted Traffic
Original language description
Asset identification plays a vital role in situational awareness building. However, the current trends in communication encryption and the emerging new protocols turn the well-known methods into a decline as they lose the necessary data to work correctly. In this paper, we examine the traffic patterns of the TLS protocol and its changes introduced in version 1.3. We train a machine learning model on TLS handshake parameters to identify the operating system of the client device and compare its results to well-known identification methods. We test the proposed method in a large wireless network. Our results show that precise operating system identification can be achieved in encrypted traffic of mobile devices and notebooks connected to the wireless network.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2020 IEEE/IFIP Network Operations and Management Symposium (NOMS 2020)
ISBN
9781728149738
ISSN
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e-ISSN
2374-9709
Number of pages
6
Pages from-to
1-6
Publisher name
IEEE Xplore Digital Library
Place of publication
Budapešť, Maďarsko
Event location
Budapešť, Maďarsko
Event date
Jan 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000716920500047