Comparative Analysis of Classification Methods and Suitable Datasets for Protocol Recognition in Operational Technologies

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU151320" target="_blank" >RIV/00216305:26220/24:PU151320 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/1999-4893/17/5/208" target="_blank" >https://www.mdpi.com/1999-4893/17/5/208</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/a17050208" target="_blank" >10.3390/a17050208</a>

Result language

angličtina

Original language name

Comparative Analysis of Classification Methods and Suitable Datasets for Protocol Recognition in Operational Technologies

Original language description

The interconnection of Operational Technology (OT) and Information Technology (IT) has created new opportunities for remote management, data storage in the cloud, real-time data transfer over long distances, or integration between different OT and IT networks. OT networks require increased attention due to the convergence of IT and OT, mainly due to the increased risk of cyber-attacks targeting these networks. This paper focuses on the analysis of different methods and data processing for protocol recognition and traffic classification in the context of OT specifics. Therefore, this paper summarizes the methods used to classify network traffic, analyzes the methods used to recognize and identify the protocol used in the industrial network, and describes machine learning methods to recognize industrial protocols. The output of this work is a comparative analysis of approaches specifically for protocol recognition and traffic classification in OT networks. In addition, publicly available datasets are compared in relation to their applicability for industrial protocol recognition. Research challenges are also identified, highlighting the lack of relevant datasets and defining directions for further research in the area of protocol recognition and classification in OT environments.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20203 - Telecommunications

Project

<a href="/en/project/FW07010004" target="_blank" >FW07010004: Utilization of Advantages of 5th Generation Network for Monitoring, Optimization and Effectiveness of Manufacturing Process in Smart Factories</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Algorithms

ISSN

1999-4893

e-ISSN

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Volume of the periodical

17

Issue of the periodical within the volume

5

Country of publishing house

CH - SWITZERLAND

Number of pages

20

Pages from-to

1-20

UT code for WoS article

001232223700001

EID of the result in the Scopus database

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