HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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The maturity of hardware virtualization has motivated communication service providers to apply this paradigm to network services. Virtual Network Functions (VNFs) come from this motivation and refer to any virtual execution environment configured to provide a given network service. VNFs constitute a new paradigm and related dependability evaluation mechanisms are still not thoroughly defined. In this paper we propose a preliminary evaluation of an anomaly detection approach applied to VNFs. Our approach uses a supervised machine learning algorithm. It notably relies on data provided by the underlying hypervisor of the VMs hosting the VNF, making it a black-box approach. Such an approach is actually well suited for infrastructure or telecommunication service providers willing to deploy tools that are easily configurable while reducing deployment costs. We validate our approach with the case study of the vIMS (IP Multimedia Subsystem) implemented by the Clearwater project.