In the continuously evolving digital landscape, risk assessment represents an essential cornerstone in cybersecurity, crucial for the identification, evaluation and prioritization of potential threats and vulnerabilities within complex digital ecosystems. Vulnerability scoring systems play a pivotal role in this process by providing structured methodologies to quantify and qualify the severity and impact of vulnerabilities. This paper presents a comprehensive comparison of various vulnerability scoring systems approaches, examining their structures, methodologies, and unique attributes. Beginning with a review of the critical role of risk assessment in the dynamic cyber threat landscape, it emphasizes the fundamental significance of vulnerability scoring systems in risk evaluation. The selection criteria for the vulnerability scoring systems that are analyzed are clarified, focusing on justifying choices based on relevance and significance while considering parameters guiding their selection. A detailed analysis of the selected vulnerability scoring systems follows, delving into methodologies, metrics, and distinct characteristics, providing an in-depth understanding of their functionalities. Subsequently, a comparative evaluation of these systems is conducted, highlighting their respective strengths, weaknesses, and overall effectiveness in cybersecurity risk assessment, while benefits and drawbacks of each vulnerability scoring system are examined to offer a comprehensive perspective. The conclusions of this comparative study bring together the results, summarizing essential insights gathered through the analysis of the vulnerability scoring systems. Overall, this paper provides a structured evaluation of the available vulnerability scoring systems, offering valuable insights for professionals in the field of cybersecurity, as well as future research involved in vulnerability management and risk assessment.

The electrical grid has significantly evolved over the years, thus creating a smart paradigm, which is well known as the smart electrical grid. However, this evolution creates critical cybersecurity risks due to the vulnerable nature of the industrial systems and the involvement of new technologies. Therefore, in this paper, the ELECTRON architecture is presented as an integrated platform to detect, mitigate and prevent potential cyberthreats timely. ELECTRON combines both cybersecurity and energy defence mechanisms in a collaborative way. The key aspects of ELECTRON are (a) dynamic risk assessment, (b) asset certification, (c) federated intrusion detection and correlation, (d) Software Defined Networking (SDN) mitigation, (e) proactive islanding and (f) cybersecurity training and certification.

The average life expectancy of the world’s population is increasing and the healthcare systems sooner than later will be compromised by its reduced capacity and its highly economic cost; in addition, the age distribution of the population is leading towards the older spectrum. This trend will lead to immeasurable and unexpected economic problems and social changes. In order to face up this challenge and complex economic and social problem, it is necessary to rely on the appropriate digital tools and technological infrastructures for ensuring that the elderly are properly cared in their everyday living environments and they can live independently for longer. This article presents ACTIVAGE IoT Ecosystem Suite (AIoTES), a concrete reference architecture and its implementation process that addresses these issues and that was designed within the first European Large Scale Pilot, ACTIVAGE, a H2020 funded project by the European Commission with the objective of creating sustainable ecosystems for Active and Healthy Ageing (AHA) based on Internet of Things and big data technologies. AIoTES offers platform level semantic interoperability, with security and privacy, as well as Big Data and Ecosystem tools. AIoTES enables and promotes the creation, exchange and adoption of cross-platform services and applications for AHA. The number of existing AHA services and solutions are quite large, especially when state-of-the-art technology is introduced, however a concrete architecture such as AIoTES gains more importance and relevance by providing a vision for establishing a complete ecosystem, that looks for supporting a larger variety of AHA services, rather than claiming to be a unique solution for all the AHA domain problems. AIoTES has been successfully validated by testing all of its components, individually, integrated, and in real-world environments with 4345 direct users. Each validation is contextualized in 11 Deployment Sites (DS) with 13 Validation Scenarios covering the heterogeneity of the AHA-IoT needs. These results also show a clear path for improvement, as well as the importance for standardization efforts in the ever-evolving AHA-IoT domain.

The Decision Support tool of the myAirCoach platform is presented in this work. MyAirCoach is a web-based platform for personalized management of asthma patients. The Decision Support tool is used from medical experts to generate knowledge-based rules for asthma patients. The tool is a web-based application that includes a simple-to-use rule editor for generating medical rules in Arden Syntax, which is an HL7 standard. The logic of the rules in formulated in disjunctive normal form. Using the this tool, medical experts can generate rules and specify the set of rules that are applicable for alerting each patient, thus creating a personalized decision support system for asthma patients.