A review on graph-based approaches for network security monitoring and botnet detection

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F24%3A00135191" target="_blank" >RIV/00216224:14610/24:00135191 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/article/10.1007/s10207-023-00742-7" target="_blank" >https://link.springer.com/article/10.1007/s10207-023-00742-7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10207-023-00742-7" target="_blank" >10.1007/s10207-023-00742-7</a>

Result language

angličtina

Original language name

A review on graph-based approaches for network security monitoring and botnet detection

Original language description

This survey paper provides a comprehensive overview of recent research and development in network security that uses graphs and graph-based data representation and analytics. The paper focuses on the graph-based representation of network traffic records and the application of graph-based analytics in intrusion detection and botnet detection. The paper aims to answer several questions related to graph-based approaches in network security, including the types of graphs used to represent network security data, the approaches used to analyze such graphs, the metrics used for detection and monitoring, and the reproducibility of existing works. The paper presents a survey of graph models used to represent, store, and visualize network security data, a survey of the algorithms and approaches used to analyze such data, and an enumeration of the most important graph features used for network security analytics for monitoring and botnet detection. The paper also discusses the challenges and limitations of using graph-based approaches in network security and identifies potential future research directions. Overall, this survey paper provides a valuable resource for researchers and practitioners in the field of network security who are interested in using graph-based approaches for analyzing and detecting malicious activities in networks.

Czech name

—

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

—

OECD FORD branch

10200 - Computer and information sciences

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)

Publication year

2024

Confidentiality

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

Name of the periodical

International Journal of Information Security

ISSN

1615-5262

e-ISSN

1615-5270

Volume of the periodical

23

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

22

Pages from-to

119-140

UT code for WoS article

001062032500001

EID of the result in the Scopus database

2-s2.0-85169463507