Cyber-physical systems are nowadays an important component of most industrial infrastructures, and materialise the integration of control systems with advanced information technologies. Commonly, they aggregate distinct communication platforms and networked devices or nodes with different capabilities and goals. The resulting increase in complexity has inevitably brought into play new challenges, namely on the physical world and cyber space. In these systems, the development and gaining of state awareness and how to deal with the inherent vulnerabilities of the overall system are essential and also challenging. In this work, the problem of resilience enhancement in cyber-physical systems is addressed based on a hierarchical multi-agent framework that is implemented over a distributed middleware, in which each agent carries out specific tasks. Physical and cyber vulnerabilities are taken into account, and state and context awarenesses of the whole system targeted. The proposed framework ensures a minimum level of acceptable performance in case of physical disturbances and malicious attacks, as demonstrated by experiments on a IPv6-based test-bed.

Supervisory Control And Data Acquisition (SCADA) systems are currently an integrating part of most critical industrial infrastructures, for which security is paramount. Given to their increasing integration with corporate networks, which the industry 4.0 is the most recent driving force, security to cyber attacks can no longer rely on the principle of isolation. In this context, the present paper intends to shed some light on the subject by addressing the problem from each SCADA system components, including its interaction with Wireless Sensor and Actuator Networks (WSANs). The problem of resilience of WSANs is here discussed by appealing to a multi-agent based approach within a distributed middleware framework.

Wireless Sensor Networks enable flexibility, low operational and maintenance costs, as well as scalability in a variety of scenarios. However, in the context of industrial monitoring scenarios the use of Wireless Sensor Networks can compromise the system's performance due to several factors, being one of them the presence of outliers in raw data. In order to improve the overall system's resilience, this paper proposes a distributed hierarchical multi-agent architecture where each agent is responsible for a specific task. This paper deals with online detection and accommodation of outliers in non-stationary time-series by appealing to a machine learning technique. The methodology is based on a Least Squares Support Vector Machine along with a sliding window-based learning algorithm. A modification to this method is considered to improve its performance in transient raw data collected from transmitters over a Wireless Sensor Networks (WSNs). An empirical study based on laboratory test-bed show the feasibility and relevance of incorporating the proposed methodology in the context of monitoring systems over Wireless Sensor Networks.

Wireless Sensor and Actuator Networks has become an important area of research. They can provide flexibility, low operational and maintenance costs and they are inherently scalable. In the realm of Internet of Things the majority of devices is able to communicate with one another, and in some cases they can be deployed with an IP address. This feature is undoubtedly very beneficial in wireless sensor and actuator networks applications, such as monitoring and control systems. However, this kind of communication infrastructure is rather challenging as it can compromise the overall system performance due to several factors, namely outliers, intermittent communication breakdown or security issues. In order to improve the overall resilience of the system, this work proposes a distributed hierarchical multi-agent architecture implemented over a IPv6 communication infrastructure. The Contiki Operating System and RPL routing protocol were used together to provide a IPv6 based communication between nodes and an external network. Experimental results collected from a laboratory IPv6 based WSAN test-bed, show the relevance and benefits of the proposed methodology to cope with communication loss between nodes and the server.

The growing developments on networked devices, with different communication platforms and capabilities, made the cyber-physical systems an integrating part of most critical industrial infrastructures. Given their increasing integration with corporate networks, in which the industry 4.0 is the most recent driving force, new uncertainties, not only from the tangible physical world, but also from a cyber space perspective, are brought into play. In order to improve the overall resilience of a cyber-physical system, this work proposes a framework based on a distributed middleware that integrates a multiagent topology, where each agent is responsible for coordinating and executing specific tasks. In this framework, both physical and cyber vulnerabilities alike are considered, and the achievement of a correct state awareness and minimum levels of acceptable operation, in response to physical or malicious disturbances, are guaranteed. Experimental results collected with an IPv6-based simulator comprising several distributed computational devices and heterogeneous communication networks show the relevance and inherent benefits of this approach.