Using Machine Learning for DNS over HTTPS Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F20%3A43902306" target="_blank" >RIV/60076658:12310/20:43902306 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21240/20:00349375
Result on the web
<a href="https://www.researchgate.net/profile/Gulfarida-Tulemisova/publication/343736857_ECCWS_Proceedings_Download/links/5f3cd398299bf13404cee480/ECCWS-Proceedings-Download.pdf" target="_blank" >https://www.researchgate.net/profile/Gulfarida-Tulemisova/publication/343736857_ECCWS_Proceedings_Download/links/5f3cd398299bf13404cee480/ECCWS-Proceedings-Download.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.34190/EWS.20.001" target="_blank" >10.34190/EWS.20.001</a>
Alternative languages
Result language
angličtina
Original language name
Using Machine Learning for DNS over HTTPS Detection
Original language description
DNS over HTTPS (DoH) is a new standard that is being adopted by most of the new versions of web-browsers. This protocol allows translating the canonical domain name to an IP address by using the HTTPS tunnel. The usage of such a protocol has many pros and cons. In our paper, we try to evaluate these aspects from different points of view. One of the most critical disadvantages lies in the much more complicated possibility of network traffic logging. Our team has created a machine learning-based approach allowing automated DoH detection, which seems to be pretty well usable in advanced firewalls.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
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
Proceedings of the 19th European Conference on Cyber Warfare and Security
ISBN
978-1-912764-61-7
ISSN
2048-8602
e-ISSN
2048-8610
Number of pages
7
Pages from-to
205-211
Publisher name
Academic Conferences and Publishing International Limited
Place of publication
Reading, UK
Event location
The University of Chester, UK
Event date
Jun 25, 2020
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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