Attack Detection in Cyber-Physical Production Systems using the Deterministic Dendritic Cell Algorithm

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2020

Autores

Pinto, R (Autor) FEUP; Gil Manuel Gonçalves (Autor) FEUP; tovar, e (Autor) Outra; Delsing, J (Autor) Outra

Ata de Conferência Internacional

Título: 25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2020, Vienna, Austria, September 8-11, 2020

Páginas: 1548-1555

Indexação

ISI Web of Knowledge - 10 Citações

Scopus - 17 Citações

Outras Informações

ID Authenticus: P-00S-W1P

DOI: 10.1109/etfa46521.2020.9212021

Abstract (EN): Cyber-Physical Production Systems (CPPS) are key enablers for industrial and economic growth. The introduction of the Internet of Things (IoT) in industrial processes represents a new revolution towards the Smart Manufacturing oncept and is usually designated as the 4th Industrial Revolution. Despite the huge interest from the industry to innovate their production systems, in order to increase revenues at lower costs, the IoT concept is still immature and fuzzy, which increases security related risks in industrial systems. Facing this paradigm and, since CPPS have reached a level of complexity, where the human intervention for operation and control is becoming increasingly difficult, Smart Factories require autonomic methodologies for security management and self-healing. This paper presents an Intrusion Detection System (IDS) approach for CPPS, based on the deterministic Dendritic Cell Algorithm (dDCA). To evaluate the dDCA effectiveness, a testing dataset was generated, by implementing and injecting various attacks on a OPC UA based CPPS testbed. The results show that these attacks can be successfully detected using the dDCA.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8