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

      Vigoya, Laura; Fernández, Diego; Carneiro, Víctor; Cacheda, Fidel (MDPI AG, 2020-07-04)
      [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 ...
    • Application of machine learning algorithms for the validation of a new CoAP-IoT anomaly detection dataset 

      Vigoya, Laura; Pardal Noya, Alberto; Fernández, Diego; Carneiro, Víctor (MDPI, 2023-04)
      [Abstract]: With the rise in smart devices, the Internet of Things (IoT) has been established as one of the preferred emerging platforms to fulfil their need for simple interconnections. The use of specific protocols such ...
    • IoT Dataset Validation Using Machine Learning Techniques for Traffic Anomaly Detection 

      Vigoya, Laura; Fernández, Diego; Carneiro, Víctor; Nóvoa, Francisco (MDPI, 2021)
      [Abstract] With advancements in engineering and science, the application of smart systems is increasing, generating a faster growth of the IoT network traffic. The limitations due to IoT restricted power and computing ...
    • Time-Aware Detection Systems 

      López-Vizcaíno, Manuel F.; Vigoya, Laura; Cacheda, Fidel; Nóvoa, Francisco (MDPI AG, 2019-08-05)
      [Abstract] Communication network data has been growing in the last decades and with the generalisation of the Internet of Things (IoT) its growth has increased. The number of attacks to this kind of infrastructures have ...