PCAPFunnel: A Tool for Rapid Exploration of Packet Capture Files
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F21%3APU142933" target="_blank" >RIV/00216305:26230/21:PU142933 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14610/21:00121642
Result on the web
<a href="https://www.fit.vut.cz/research/publication/12556/" target="_blank" >https://www.fit.vut.cz/research/publication/12556/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IV53921.2021.00021" target="_blank" >10.1109/IV53921.2021.00021</a>
Alternative languages
Result language
angličtina
Original language name
PCAPFunnel: A Tool for Rapid Exploration of Packet Capture Files
Original language description
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 web-based - 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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2021 25TH INTERNATIONAL CONFERENCE INFORMATION VISUALISATION (IV): AI & VISUAL ANALYTICS & DATA SCIENCE
ISBN
978-1-6654-3827-8
ISSN
2375-0138
e-ISSN
—
Number of pages
8
Pages from-to
69-76
Publisher name
IEEE Biometric Council
Place of publication
Sydney
Event location
Sydney
Event date
Jul 5, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000850000500011