Since cyber-attacks are ever-increasing in number, intensity, and variety, a strong need for a global, standardized cyber-security knowledge database has emerged as a means to prevent and fight cybercrime. Attempts already exist in this regard. The Common Vulnerabilities and Exposures (CVE) list documents numerous reported software and hardware vulnerabilities, thus building a community-based dictionary of existing threats. The MITRE ATT&CK Framework describes adversary behavior and offers mitigation strategies for each reported attack pattern. While extremely powerful on their own, the tremendous extra benefit gained when linking these tools cannot be overlooked. This paper introduces a dataset of 1813 CVEs annotated with all corresponding MITRE ATT&CK techniques and proposes models to automatically link a CVE to one or more techniques based on the text description from the CVE metadata. We establish a strong baseline that considers classical machine learning models and state-of-the-art pre-trained BERT-based language models while counteracting the highly imbalanced training set with data augmentation strategies based on the TextAttack framework. We obtain promising results, as the best model achieved an F1-score of 47.84%. In addition, we perform a qualitative analysis that uses Lime explanations to point out limitations and potential inconsistencies in CVE descriptions. Our model plays a critical role in finding kill chain scenarios inside complex infrastructures and enables the prioritization of CVE patching by the threat level. We publicly release our code together with the dataset of annotated CVEs.

This study presents a global analysis of research priorities for technologies relevant to Sustainable Development Goals (SDGs). We examine 18 technological domains across countries, introducing a novel within-country rank metric to normalize differences in research output. Using a combination of linear regression and K-means cluster analysis, we identify factors influencing overall productivity and reveal distinct patterns in research priorities among nations. Our analysis of Web of Science total publication data yields five country clusters with specific technological focus areas: Eco-Tech Innovators, Cyber-Digital Architects, Bio-Industrial Pioneers, Geo-Data Security Analysts, and Cyber-Sustainable Integrators. We find that while economic indicators strongly predict overall research productivity, countries with similar economic profiles often exhibit divergent research priorities. Artificial Intelligence emerges as a top priority across all clusters, while areas such as blockchain and digital twins show lower prioritization despite their theoretical importance. Our findings reveal unexpected similarities in research focus among geopolitically diverse countries and highlight regional patterns in technological emphasis. This study offers valuable information for policymakers and researchers, enhancing our understanding of the global landscape of SDG-relevant technological research and potential avenues for international collaboration.

This study investigates the landscape of cyber-financial risks across Europe by identifying distinct risk profiles based on financial literacy, digital comfort, and economic vulnerability. Utilizing data from the Flash Eurobarometer 525 survey, we employ K-means cluster analysis to categorize European citizens into five distinct cyber-financial risk profiles: Cyber-Savvy Pragmatists, Digital-Savvy Vulnerable individuals, Cautious Traditionalists, Comfortably Naive individuals, and Digitally Hesitant At-Risk individuals. Our findings show significant variations in risk profiles across demographic groups and European regions, with gender disparities and educational differences. We examine how self-perceived financial knowledge and financial decision-making patterns differ across these profiles, uncovering potential overconfidence in some groups that may exacerbate cyber-financial vulnerabilities. This study also explores regional distributions of risk profiles, highlighting areas of heightened cybersecurity concern across Europe. Our results indicate that cybersecurity strategies should be tailored to address the specific vulnerabilities of each risk profile, with particular attention to gender-based disparities and regional variations. This research contributes to a better understanding of cyber-financial risks in Europe and offers actionable information for policymakers, financial institutions, and cybersecurity professionals in developing targeted interventions to enhance digital financial security across diverse populations.

This article examines configurations of digital concerns within the European Union (EU27), a leading hub of innovation and policy development. The core objective is to uncover the social forces shaping technology acceptance and risk awareness, which are essential for fostering a resilient digital society in the EU. The study draws upon Bourdieu’s concept of capital to discuss technological capital and digital habitus and Beck’s risk society theory to frame the analysis of individual and national attitudes towards digital risks. Utilizing Eurobarometer data, the research operationalizes technological capital through proxy indicators of individual socioeconomic status and internet use, while country-level development indicators are used to predict aggregated national risk perception. Article contributions rely on individual- and country-level statistical analysis. Specifically, the study reveals that digital concerns are better predicted at a national level rather than individual level, being shaped by infrastructure, policy, and narrative rather than by personal technological capital. Key findings highlight a positive and a negative correlation between digital advancement with cybersecurity fears and digital literacy, respectively. HDI and DESI are relevant country-level predictors of public concerns, while CGI values are not. Using cluster analysis, we identify and interpret four digital risk cultures within the EU, each with varying foci and levels of concern, which correspond to economic, political, and cultural influences at the national level.

The IoT market has grown significantly in recent years, and it is estimated that it will continue to do so. For this reason, the need to identify new solutions to ensure security is vital for the future development in this field. Inadequate sources of entropy are one of the factors that negatively influence security. In this study, inspired by NIST’s latest entropy estimation recommendations, we proposed a methodology for analyzing and validating a sensor-based entropy source, highlighted by an innovative experiment design. Moreover, the proposed solution is analyzed in terms of resistance to multiple types of attacks. Following an analysis of the influence of sensor characteristics and settings on the entropy rate, we obtain a maximum entropy value of 0.63 per bit, and a throughput of 3.12 Kb/s, even when no motion is applied on the sensors. Our results show that a stable and resistant entropy source can be built based on the data obtained from the sensors. Our assessment of the proposed entropy source also achieves a higher complexity than previous studies, in terms of the variety of approached situations and the types of the performed experiments.

This paper documents the change and reproduction of gender status in the motion picture industry by discussing patterns in protagonist choice and authorship of biographical films produced from 1900 to 2017. The results rely on a quantitative analysis of all 4,539 films on the IMDb platform labeled with the “Biography” tag that portray an individual main character in the selected years. We find that men-only filmmaking teams have been remarkably consistent from 1900 onward in their choice of male subjects, while mixed and women-only teams have driven an increase in the central representation of women as figures whose life is worthy of narration and remembrance. Therefore, the recently increased involvement of women as directors has significantly advanced the symbolic recognition of women in public cinematographic discourse. Our findings document the emergence of a transitional period in the biographical movie industry in which the reproduction of gender status asymmetries coexists with an increased participation of women in filmmaking.