Research on cybersecurity security skills is highly relevant in today's digital era, where cybersecurity threats are growing in complexity and frequency. This study aims to evaluate and contrast multiple EU-based cybersecurity skills frameworks to highlight areas of convergence, divergence, and potential gaps, offering valuable insights for improving the cohesion and applicability of these frameworks. It was applied a qualitative content analysis approach combined with a comparative analysis technique. This approach is used to identify the main cybersecurity skills emphasized across EU-based cybersecurity frameworks, exploring how they differ in terms of structure, scope, and focus areas, and discovering the main strengths and limitations of these frameworks. The findings support the creation of more inclusive and adaptive frameworks that address underrepresented areas, such as the needs of small and medium-sized enterprises (SMEs) and emerging domains like AI security. Overall, this study serves as a foundational resource for enhancing cybersecurity resilience, promoting skills standardization, and advancing the EU's leadership in global cybersecurity preparedness. © 2025

Purpose Security in large-scale agile is a crucial aspect that should be carefully addressed to ensure the protection of sensitive data, systems and user privacy. This study aims to identify and characterize the security practices that can be applied in managing large-scale agile projects. Design/methodology/approach A qualitative study is carried out through 18 interviews with 6 software development companies based in Portugal. Professionals who play the roles of Product Owner, Scrum Master and Scrum Member were interviewed. A thematic analysis was applied to identify deductive and inductive security practices. Findings The findings identified a total of 15 security practices, of which 8 are deductive themes and 7 are inductive. Most common security practices in large-scale agile include penetration testing, sensitive data management, automated testing, threat modeling and the implementation of a DevSecOps approach. Originality/value The results of this study extend the knowledge about large-scale security practices and offer relevant practical contributions for organizations that are migrating to large-scale agile environments. By incorporating security practices at every stage of the agile development lifecycle and fostering a security-conscious culture, organizations can effectively address security challenges in large-scale agile environments.

Abstract High-performance computing (HPC) plays a crucial role in accelerating digital transformation, yet there is a lack of studies that systematically characterize its impact across different company sizes. This study addresses this gap by analyzing a cross-sectoral panel of 294 Portuguese companies, comprising 103 large enterprises and 191 small- and medium-sized enterprises (SMEs). It was applied descriptive analysis and statistical hypothesis testing methods. Two key research questions guide this investigation. The first explores the primary benefits and challenges associated with HPC adoption, while the second examines whether these factors vary between large companies and SMEs. The findings indicate that the benefits and challenges of the HPC are heterogeneously perceived by large companies and SMEs. It identified significant differences in the perceived benefits and challenges of HPC, particularly concerning cost savings, decision-making, cost and skills management, lack of awareness, and workforce skills gap. These findings contribute to a deeper understanding of how HPC supports digitalization processes, highlighting sector-specific and size-dependent differences in its perceived value and implementation barriers. This study provides valuable insights for businesses, policymakers, and researchers seeking to optimize HPC strategies for digital transformation.

Purpose This paper aims to explore the changes imposed by the general data protection regulation (GDPR) on software engineering practices. The fundamental objective is to have a perception of the practices and phases that have experienced the greatest changes. Additionally, it aims to identify a set of good practices that can be adopted by software engineering companies. Design/methodology/approach This study uses a qualitative methodology through four case studies involving Portuguese software engineering companies. Two of these companies are small and medium enterprises (SMEs) while the other remaining two are micro-companies. The thematic analysis is adopted to identify patterns in the performed interviews. Findings The findings indicate that significant changes have occurred at all stages of software development. In particular, the initial stages of identifying requirements and modeling processes were the stages that experienced the greatest changes. On the opposite, the technical development phase has not noticeably changed but, nevertheless, it is necessary to look at the importance of training software developers for GDPR rules and practices. Research limitations/implications Two relevant limitations were identified as follows: only four case studies involving micro-companies and SMEs were considered, and only the traditional software development methodology was considered. The use of agile methodologies was not explored in this study and the findings can only be mainly applied to the waterfall model. Originality/value This study offers mainly practical contributions by identifying a set of challenges that are posed to software engineering companies by the implementation of GDPR. Through their knowledge, it is expected to help these companies to better prepare themselves and anticipate the challenges they will necessarily face.

The project XPRESS introduces a completely new scalable concept of an expertonic networked factory, which is composed by a coordinated team of specialized autonomous entities (intelligent production units), each knowing how to do a certain process optimally. This paper looks in particular to the transport intelligent unit implementation, which is responsible for the transportation of components at the shop-floor. An architecture based in a multi-agent approach that uses automatic guided vehicle expertons to perform this task is suggested. Additionally, it is presented an implementation of the automatic guided vehicle transport intelligent unit that uses the .NET framework integrated with the expertonic framework.