Using Machine Learning for DNS over HTTPS Detection

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F20%3A00349375" target="_blank" >RIV/68407700:21240/20:00349375 - isvavai.cz</a>
Alternative codes found
RIV/60076658:12310/20:43902306
Result on the web
<a href="https://doi.org/10.34190/EWS.20.001" target="_blank" >https://doi.org/10.34190/EWS.20.001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.34190/EWS.20.001" target="_blank" >10.34190/EWS.20.001</a>

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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Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of European Conference on Cyber Warfare and Security (ECCWS 2020)
ISBN
9781912764617
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
205-211
Publisher name
Academic Conferences and Publishing International Ltd.
Place of publication
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Event location
Chester
Event date
Jun 25, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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