Application of distributed computing and machine learning technologies to cybersecurity
SHIELD is a distributed cyber-security system that leverages Network Function Virtualisation for dynamically deploying virtual Network Security Functions. The security functions send network traffic’s monitoring data to a bigdata store. The Data Analysis and Remediation Engine executes security anal...
| Autores: | , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:2072/531537 |
| Acceso en línea: | http://hdl.handle.net/2072/531537 https://zenodo.org/badge/DOI/10.5281/zenodo.3266038.svg |
| Access Level: | acceso abierto |
| Palabra clave: | Xarxes d'àrea extensa (Ordinadors) Distributed Artificial Intelligence Security Cybersecurity Artificial Intelligence & Big Data Network Functions Virtualisation 621.3 |
| Sumario: | SHIELD is a distributed cyber-security system that leverages Network Function Virtualisation for dynamically deploying virtual Network Security Functions. The security functions send network traffic’s monitoring data to a bigdata store. The Data Analysis and Remediation Engine executes security analytics modules on top of monitoring data modules in order to detect threats. The security analytics heavily leverage Machine Learning algorithms for detecting anomalies and classifying threats. This paper presents the different Machine Learning algorithms and details the obtained results and the direction taken by the project with regards to its implementation, including business capabilities for the cybersecurity solution. |
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