InSight2: A Modular Visual Analysis Platform For Network Situational Awareness in Large-Scale Networks
| Autor: | Hansaka Angel Dias Edirisinghe Kodituwakku, Alex Keller, Jens Gregor |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Visual analytics
Situation awareness Computer Networks and Communications Computer science Distributed computing lcsh:TK7800-8360 Throughput 02 engineering and technology visual analytics incident response 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Flexibility (engineering) business.industry lcsh:Electronics 020206 networking & telecommunications Flow network anomaly detection cybersecurity awareness Hardware and Architecture Control and Systems Engineering Analytics Signal Processing Scalability 020201 artificial intelligence & image processing Anomaly detection business |
| Zdroj: | Electronics, Vol 9, Iss 1747, p 1747 (2020) Electronics Volume 9 Issue 10 |
| ISSN: | 2079-9292 |
| Popis: | The complexity and throughput of computer networks are rapidly increasing as a result of the proliferation of interconnected devices, data-driven applications, and remote working. Providing situational awareness for computer networks requires monitoring and analysis of network data to understand normal activity and identify abnormal activity. A scalable platform to process and visualize data in real time for large-scale networks enables security analysts and researchers to not only monitor and study network flow data but also experiment and develop novel analytics. In this paper, we introduce InSight2, an open-source platform for manipulating both streaming and archived network flow data in real time that aims to address the issues of existing solutions such as scalability, extendability, and flexibility. Case-studies are provided that demonstrate applications in monitoring network activity, identifying network attacks and compromised hosts and anomaly detection. |
| Databáze: | OpenAIRE |
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