D 2021

Stream-Based IP Flow Analysis

ČERMÁK, Milan and Pavel ČELEDA

Basic information

Original name

Stream-Based IP Flow Analysis

Authors

ČERMÁK, Milan and Pavel ČELEDA

Edition

Bordeaux, France, IFIP/IEEE International Symposium on Integrated Network Management, IM 2021, p. 736-741, 6 pp. 2021

Publisher

IFIP Open Digital Library

Other information

Language

English

Type of outcome

Proceedings paper

Country of publisher

United States of America

Confidentiality degree

is not subject to a state or trade secret

Publication form

electronic version available online

References:

Organization

Ústav výpočetní techniky – Repository – Repository

ISBN

978-3-903176-32-4

UT WoS

000696801700108

EID Scopus

2-s2.0-85113673996

Keywords in English

Stream Processing; IP Flow; Stream4Flow

Links

EF16_019/0000822, research and development project.
Changed: 18/4/2022 02:36, RNDr. Daniel Jakubík

Abstract

V originále

As the complexity of Internet services, transmission speed, and data volume increases, current IP flow monitoring and analysis approaches cease to be sufficient, especially within high-speed and large-scale networks. Although IP flows consist only of selected network traffic features, their processing faces high computational demands, analysis delays, and large storage requirements. To address these challenges, we propose to improve the IP flow monitoring workflow by stream-based collection and analysis of IP flows utilizing a distributed data stream processing. This approach requires changing the paradigm of IP flow data monitoring and analysis, which is the main goal of our research. We analyze distributed stream processing systems, for which we design a novel performance benchmark to determine their suitability for stream-based processing of IP flow data. We define a stream-based workflow of IP flow collection and analysis based on the benchmark results, which we also implement as a publicly available and open-source framework Stream4Flow. Furthermore, we propose new analytical methods that leverage the stream-based IP flow data processing approach and extend network monitoring and threat detection capabilities.

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