Annotated Dataset for Anomaly Detection in a Data Center with IoT Sensors.

ABSTRACT: The relative simplicity of IoT networks extends service vulnerabilities and possibilities to different network failures exhibiting system weaknesses. Therefore, having a dataset with a sufficient number of samples, labeled and with a systematic analysis, is essential in order to understand how these networks behave and detect traffic anomalies. This work presents DAD: a complete and labeled IoT dataset containing a reproduction of certain real-world behaviors as seen from the network. To approximate the dataset to a real environment, the data were obtained from a physical data center, with temperature sensors based on NFC smart passive sensor technology. Having carried out different approaches, performing mathematical modeling using time series was finally chosen. The virtual infrastructur

SUBMITTER: Vigoya L 

PROVIDER: S-EPMC7374380 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature