Produção Nacional
Detection of Anomalies Related to the Operation of the Profinet Network Through Feature Extraction and Classification
2018; Institute of Electrical and Electronics Engineers; Volume: 16; Issue: 7 Linguagem: Inglês
10.1109/tla.2018.8447349
ISSN1548-0992
AutoresGuilherme Serpa Sestito, Afonso Celso Turcato, André Luís Dias, Rogério Andrade Flauzino, Dennis Brandão,
Tópico(s)Anomaly Detection Techniques and Applications
ResumoPROFINET networks are increasingly being applied in industrial environments. Due to its expansion, it is common for new diagnostic tools to emerge dedicated to protocol. Being more specific, it would be of the most importance if, by means of network traffic analysis, it was possible to identify the network's operating status (normal operation or with some anomaly) automatically. In view of the facts, this article aims to propose a methodology for classifying events related to the operation of the PROFINET network through feature extraction and classification with Artificial Neural Networks. All the data are real and they were collected in an industrial plant.
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