Internet of Things (IoT) is a concept adopted in nearly every aspect of human life, leading to an explosive utilization of intelligent devices. Notably, such solutions are especially integrated in the industrial sector, to allow the remote monitoring and control of critical infrastructure. Such global integration of IoT solutions has led to an expanded attack surface against IoT-enabled infrastructures. Artificial intelligence and machine learning have demonstrated their ability to resolve issues that would have been impossible or difficult to address otherwise; thus, such solutions are closely associated with securing IoT. Classical collaborative and distributed machine learning approaches are known to compromise sensitive information. In our paper, we demonstrate the creation of a network flow-based Intrusion Detection System (IDS) aiming to protecting critical infrastructures, stemming from the pairing of two machine learning techniques, namely, federated learning and active learning. The former is utilized for privately training models in federation, while the latter is a semi-supervised approach applied for global model adaptation to each of the participant’s traffic. Experimental results indicate that global models perform significantly better for each participant, when locally personalized with just a few active learning queries. Specifically, we demonstrate how the accuracy increase can reach 7.07% in only 10 queries.

As the complexity of electric systems increases, so does the required effort for the monitoring and management of grid operations. To solve grid performance issues, smart grids require the exchange of higher volumes of data, high availability of the telecommunication infrastructure, and very low latency. The fifth generation (5G) mobile network seems to be the most promising technology to support such requirements, allowing utilities to have dedicated virtual slices of network resources to maximize the service availability in case of network congestions. Regarding this evolving scenario, this work presents the Smart5Grid project vision on how 5G can support the energy vertical industry for the fast deployment of innovative digital services. Specifically, this work introduces the concept of network applications (NetApps), a new paradigm of virtualization that are envisioned to facilitate the creation of a new market for information technology (IT), small and medium enterprises (SMEs), and startups. This concept, and the open architecture that facilitates its implementation, is showcased by four real-life 5G-enabled demonstrators: (1) automatic fault detection in a medium voltage (MV) grid in Italy, (2) real-time safety monitoring for operators in high voltage (HV) substations in Spain, (3) remote distributed energy resources (DER) monitoring in Bulgaria, and (4) wide area monitoring in a cross-border scenario between Greece and Bulgaria.

Information security attacks targeting human nature, such as phishing, are rising rapidly. Information security Awareness (ISA) programs have been proven to be valuable proactive measures that increase Return On Investment (ROI) regarding information security enhancement. These programs tend to focus on concepts and technical aspects. Although these customary instruction methodologies have their preferences, trainees can additionally take advantage of educational techniques that are more intuitive and situation driven. This study aims to increase the efficiency of learning in such programmes by using design science to create an artefact for learning and then testing the acquired knowledge. Design science will be used as a research method. The creative method, a brainstorming technique, and five steps in design science are performed: explicate the problem, define requirements, design and develop artefact, demonstrate artefact, and evaluate artefact to develop a process framework to respond to this problem. The problem is explicated with a literature review and the requirements to be met by Game-Based Learning (GBL) are set. The first artefact, which is an interactive book support quizzes, crossword puzzles, multimedia such as video, and “complete the word” simple games that enhance the learning process. The second artefact is a printed board game with hackers and cards with the goal to support the learning process and assess the ability of the participants to respond and take actions based on this new knowledge. At last, limitations that exist in security education such as lack of user-centered modules and limited guidelines from learning theories are elaborated and future work is also presented.