Using Network Traces to Generate Models for Automatic Network Application Protocols Diagnostics

Holkovič, Martin; Ryšavý, Ondřej; Polčák, Libor

doi:10.5220/0007929900370047

Cited by 2 publications

(1 citation statement)

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“…Automatic diagnostic tools process the captured network traffic, try to identify network issues, and report them [7], [11], [12]. A common strategy is that the administrators validate these reports and take countermeasures if necessary.…”

Section: B Network Traffic Analysismentioning

confidence: 99%

PCAPFunnel: A Tool for Rapid Exploration of Packet Capture Files

Uhlar

Holkovič

Rusňák

2021

2021 25th International Conference Information Visualisation (IV)

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Analyzing network traffic is one of the fundamental tasks in both network operations and security incident analysis. Despite the immense efforts in workflow automation, an ample portion of the work still relies on manual data exploration and analytical insights by domain specialists. Current state-of-the-art network analysis tools provide high flexibility at the expense of usability and have a steep learning curve. Recent-often webbased-analytical tools emphasize interactive visualizations and provide simple user interfaces but only limited analytical support. This paper describes the tool that supports the analytical work of network and security operators. We introduce typical user tasks and requirements. We also present the filtering funnel metaphor for exploring packet capture (PCAP) files through visualizations of linked filter steps. We have created PCAPFunnel, a novel tool that improves the user experience and speeds up packet capture data analysis. The tool provides an overview of the communication, intuitive data filtering, and details of individual network nodes and connections between them. The qualitative usability study with nine domain experts confirmed the usability and usefulness of our approach for the initial data exploration in a wide range of tasks and usage scenarios, from educational purposes to exploratory network data analysis.

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Section: B Network Traffic Analysismentioning

confidence: 99%