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A Real-Time Streaming System for Customized Network Traffic Capture †

Logging network traffic offers valuable insights into data flow, enabling the proactive analysis and troubleshooting of issues as they arise. Moreover, it provides a means to access and examine the exchanged information among network users that would otherwise be inaccessible. To enhance network tra...

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Detalles Bibliográficos
Autores principales: Costin, Adrian-Tiberiu, Zinca, Daniel, Dobrota, Virgil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383574/
https://www.ncbi.nlm.nih.gov/pubmed/37514759
http://dx.doi.org/10.3390/s23146467
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author Costin, Adrian-Tiberiu
Zinca, Daniel
Dobrota, Virgil
author_facet Costin, Adrian-Tiberiu
Zinca, Daniel
Dobrota, Virgil
author_sort Costin, Adrian-Tiberiu
collection PubMed
description Logging network traffic offers valuable insights into data flow, enabling the proactive analysis and troubleshooting of issues as they arise. Moreover, it provides a means to access and examine the exchanged information among network users that would otherwise be inaccessible. To enhance network traffic analysis, the integration of innovative technologies that facilitate real-time querying and pattern matching proves indispensable. This research paper presents a system that exemplifies such advancements—an innovative network traffic logging tool. The tool specifically focuses on performing real-time network packet transfer to Apache Kafka and ksqlDB, leveraging their capabilities to ensure swift and dependable storage of network packets in Apache Kafka topics. By showcasing this solution, the paper demonstrates the benefits and effectiveness of employing modern technologies for network traffic analysis and management.
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spelling pubmed-103835742023-07-30 A Real-Time Streaming System for Customized Network Traffic Capture † Costin, Adrian-Tiberiu Zinca, Daniel Dobrota, Virgil Sensors (Basel) Article Logging network traffic offers valuable insights into data flow, enabling the proactive analysis and troubleshooting of issues as they arise. Moreover, it provides a means to access and examine the exchanged information among network users that would otherwise be inaccessible. To enhance network traffic analysis, the integration of innovative technologies that facilitate real-time querying and pattern matching proves indispensable. This research paper presents a system that exemplifies such advancements—an innovative network traffic logging tool. The tool specifically focuses on performing real-time network packet transfer to Apache Kafka and ksqlDB, leveraging their capabilities to ensure swift and dependable storage of network packets in Apache Kafka topics. By showcasing this solution, the paper demonstrates the benefits and effectiveness of employing modern technologies for network traffic analysis and management. MDPI 2023-07-17 /pmc/articles/PMC10383574/ /pubmed/37514759 http://dx.doi.org/10.3390/s23146467 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Costin, Adrian-Tiberiu
Zinca, Daniel
Dobrota, Virgil
A Real-Time Streaming System for Customized Network Traffic Capture †
title A Real-Time Streaming System for Customized Network Traffic Capture †
title_full A Real-Time Streaming System for Customized Network Traffic Capture †
title_fullStr A Real-Time Streaming System for Customized Network Traffic Capture †
title_full_unstemmed A Real-Time Streaming System for Customized Network Traffic Capture †
title_short A Real-Time Streaming System for Customized Network Traffic Capture †
title_sort real-time streaming system for customized network traffic capture †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383574/
https://www.ncbi.nlm.nih.gov/pubmed/37514759
http://dx.doi.org/10.3390/s23146467
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