One main foundation of the Industry 4.0 is the connectivity of devices and systems using
Internet of Things technologies, where Cyber-physical systems (CPS) act as the backbone
infrastructure based on distributed and decentralized structures. CPS requires the use of
Artificial Intelligence (AI) techniques, such as Multi-Agent Systems (MAS), allowing the
incorporation of intelligence into the CPS through autonomous, proactive and cooperative
entities. The adoption of this new generation of systems in the industrial environment
opens new doors for various attacks that can cause serious damage to industrial production
systems.
This work presents the development of security mechanisms for systems based on MAS,
where these mechanisms are used in an experimental case study that consists of a multiagent
cyber-physical conveyor system. For this purpose, simple security mechanisms were
employed in the system, such as user authentication, signature and message encryption,
as well as other more complex mechanisms, such as machine learning techniques that
allows the agents to be more intelligent in relation to the exchange of messages protecting
the system against attacks, through the classification of the messages as reliable or not,
and also an intrusion detection system was carried out.
Based on the obtained results, the efficient protection of the system was reached,
mitigating the main attack vectors present in the system architecture.
