Antonio Ruiz-Martínez

Nowadays, websites employ multiple tracking mechanisms to personalize user experiences and deliver targeted advertisements. While cookies remain the dominant tracking tool, recent trends indicate an increasing adoption of stateless fingerprinting based on JavaScript methods. However, existing studies often focus on specific tracking technologies, while detailed analyses that jointly examine multiple stateful and stateless tracking mechanisms remain limited. To address this gap, we enhanced OpenWPM-Data-Analytics to improve the detection of fingerprinting mechanisms in scans performed with OpenWPM, a widely used framework for web privacy measurement studies. Using this enhanced measurement and analysis pipeline, we conducted an empirical analysis of the top 1000 most-visited websites, jointly examining cookies, web storage, web analytics tools, and browser fingerprinting techniques. The results show that stateful tracking methods such as cookies and web storage remain highly prevalent. However, fingerprinting techniques were detected on nearly one third of the analyzed websites, with JavaScript Enumeration and WebGL being the most common mechanisms. This prevalence is higher than that reported in previous automated studies, suggesting a growing reliance on fingerprinting as third-party cookies face increasing restrictions. In addition, web analytics tools were present in half of the websites analyzed. These findings highlight the growing complexity of modern web tracking and the need to improve current detection and mitigation strategies, particularly against fingerprinting mechanisms that are more difficult to block and regulate.

La Competencia Digital Docente destaca como componente esencial para asegurar una transformación educativa efectiva, y aunque existen marcos y protocolos supra institucionales, la definición y contextualización de esos instrumentos no ha sido una labor emprendida de forma sistemática por las instituciones de Educación Superior. Este estudio documenta el desarrollo del Marco de Competencia Digital Docente Universitario (ANONIMIZADO) y su protocolo de acreditación, realizado por un consorcio de 34 universidades españolas (agrupadas en el proyecto ANONIMIZADO), mediante un proceso que involucró la recolección de antecedentes, un proceso de adaptación institucional con equipos de todas las instituciones involucradas y una revisión por parte de 13 personas expertas que participaron en entrevistas semiestructuradas. La documentación del proceso y de sus resultados, detallados en este artículo, puede servir de referencia para otras instituciones que busquen desarrollar o contextualizar consistentemente sus propios marcos de competencia digital o adaptar otros marcos ya existentes.

Health data is one of the most sensitive data for people, which attracts the attention of malicious activities. We propose an open-source health data management framework, that follows a patient-centric approach. The proposed framework implements the Self-Sovereign Identity paradigm with innovative technologies such as Decentralized Identifiers and Verifiable Credentials. The framework uses Blockchain technology to provide immutability, verifiable data registry, and auditability, as well as an agent-based model to provide protection and privacy for the patient data. We also define different use cases regarding the daily patient-practitioner-laboratory interactions and specific functions to cover patient data loss, data access revocation, and emergency cases where patients are unable to give consent and access to their data. To address this design, a proof of concept is created with an interaction between patient and doctor. The most feasible technologies are selected and the created design is validated. We discuss the differences and novelties of this framework, which includes the patient-centric approach also for data storage, the designed recovery and emergency plan, the defined backup procedure, and the selected blockchain platform.

Privacy awareness has increased in recent years. In many countries, websites warn users about their use of cookies and Web browsers provide mechanisms to protect user privacy. However, it is not easy for users to understand tracking risks associated with browsing a given website. To address this, several privacy scanners have emerged to evaluate the privacy practices of websites. However, the scores these scanners provide are often limited to a small number of Web tracking indicators and are thus incomplete. To overcome this limitation, in this paper, we present WebTrackingScore, which provides users with a simple and intuitive indication of the privacy risk associated with visiting a website from a tracking perspective. Its design is based on an in-depth analysis of tracking mechanisms and the behaviour of some of the most frequently visited sites. Based on WebTrackingScore, we have analysed how the most popular websites are classified.

The clinical environment is one of the most important sources of sensitive patient data in healthcare. These data have attracted cybercriminals who pursue the theft of this information for personal gain. Therefore, protecting these data is a critical issue. This paper focuses on an analysis of the clinical environment, presents its general ecosystem and stakeholders, and inspects the main protocols implemented between the clinical components from a security and privacy perspective. Additionally, this article defines a complete use case to describe the typical workflow within a clinical setting: the life cycle of a patient sample. Moreover, we present and categorize crucial clinical information and divide it into two sensitivity levels: High and Very Sensitive, while considering the severe risks of cybercriminal access. The threat model for the use case has also been identified, in conjunction with the use case’s security and privacy needs. This work served us as basis to develop the minimum security and privacy requirements to protect the use case. Accordingly, we have defined protection mechanisms for each sensitivity level with the enabling technologies needed to satisfy each requirement. Finally, the main challenges and future steps for the use case are presented.

Currently, healthcare is critical environment in our society, which attracts attention to malicious activities and has caused an important number of damaging attacks. In parallel, the recent advancements in technologies, computing systems, and wireless communications are changing healthcare environment by adding different improvements and complexity to it. This article reviews the current state of the literature and provides a holistic view of cybersecurity in healthcare. With this purpose in mind, the article enumerates the main stakeholders and architecture implemented in the healthcare environment, as well as the main security issues (threats, attacks, etc.) produced in healthcare. In this context, this work maps the threats collected with a widely used knowledge-based framework, MITRE ATT&CK, building a contribution not seen so far. This article also enumerates the security mechanisms created to protect healthcare, identifying the principal research lines addressed in the literature, and listing the available public security-focused datasets used in machine-learning to provide security in the medical domain. To conclude, the research challenges that need to be addressed for future research works in this area are presented.

Surveys in mobile learning developed so far have analysed in a global way the effects on the usage of mobile devices by means of general apps or apps already developed. However, more and more teachers are developing their own apps to address issues not covered by existing m-learning apps. In this article, by means of a systematic literature review that covers 62 publications placed in the hype of teacher-created m-learning apps (between 2012 and 2017, the early adopters) and the usage of 71 apps, we have analysed the use of specific m-learning apps. Our results show that apps have been used both out of the classroom to develop autonomous learning or field trips, and in the classroom, mainly, for collaborative activities. The experiences analysed only develop low level outcomes and the results obtained are positive improving learning, learning performance, and attitude. As a conclusion of this study is that the results obtained with specific developed apps are quite similar to previous general surveys and that the development of long-term experiences are required to determine the real effect of instructional designs based on mobile devices. These designs should also be oriented to evaluate high level skills and take advantage of mobile features of mobile devices to develop learning activities that be made anytime at anyplace and taking into account context and realistic situations. Furthermore, it is considered relevant the study of the role of educational mobile development frameworks in facilitating teachers the development of m-learning apps.

Electronic (mobile) payment systems are an important aspect of e-commerce. However, few reviews highlight the most significant findings and challenges. In this article, we have prepared a bibliometric analysis to provide a statistical overview of previously published research papers on electronic (mobile) payment systems and user preferences, with a particular emphasis on their diverse techniques and analyses, as well as comprehensive and reliable directions to reveal evolutionary nuances and highlighting emerging areas in this specific research. This study reviewed 177 scientific papers published between 2001 and November 2021 in the Web of Science (WoS) database on the subjects of electronic payment systems (EPS) and mobile payment systems (MPS), payment interface (PI), technology acceptance model (TAM), payment frameworks (PF), and user preferences (UP). The amount of studies using the abovementioned topics (EPS, MPS, TAM, PF, and UP) increases annually. Spain, China, and Malaysia are the three main countries that actively participate, and their international academic partnership is relatively close. We have compiled a list of the most relevant publications, prolific authors, institutions, and leading research topics. The articles were used to evaluate bibliometric indicators, analyze research activity, investigate the subject’s evolution, and identify the most interconnected themes. The findings provide a comprehensive overview of existing thematic studies, with a notable rising trend showing the potential for future research in the field. The study provides a guideline for further research.