DNS over HTTPS Detection Using Standard Flow Telemetry

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F23%3APU149365" target="_blank" >RIV/00216305:26230/23:PU149365 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21240/23:00367712 RIV/63839172:_____/23:10133606
Result on the web
<a href="https://ieeexplore.ieee.org/abstract/document/10123708" target="_blank" >https://ieeexplore.ieee.org/abstract/document/10123708</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2023.3275744" target="_blank" >10.1109/ACCESS.2023.3275744</a>

Result language
angličtina
Original language name
DNS over HTTPS Detection Using Standard Flow Telemetry
Original language description
The aim of DNS over HTTPS (DoH) is to enhance users’ privacy by encrypting DNS. However, it also enables adversaries to bypass security mechanisms that rely on inspecting unencrypted DNS. Therefore in some networks, it is crucial to detect and block DoH to maintain security. Unfortunately, DoH is particularly challenging to detect, because it is designed to blend into regular HTTPS traffic. So far, there have been numerous proposals for DoH detection; however, they rely on specialized flow monitoring software that can export complex features that cannot be often computed on the running sequence or suffer from low accuracy. These properties significantly limit their mass deployment into real-world environments. Therefore this study proposes a novel DoH detector that uses IP-based, machine learning, and active probing techniques to detect DoH effectively with standard flow monitoring software. The use of classical flow features also enables its deployment in any network infrastructure with flow-monitoring appliances such as intelligent switches, firewalls, or routers. The proposed approach was tested using lab-created and real-world ISP-based network data and achieved a high classification accuracy of 0.999 and an F1 score of 0.998 with no false positives.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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)

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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