The usage of cybersecurity is growing steadily because it is beneficial to us. When people use cybersecurity, they can easily protect their valuable data. Today, everyone is connected through the internet. It’s much easier for a thief to connect important data through cyber-attacks. Everyone needs cybersecurity to protect their precious personal data and sustainable infrastructure development in data science. However, systems protecting our data using the existing cybersecurity systems is difficult. There are different types of cybersecurity threats. It can be phishing, malware, ransomware, and so on. To prevent these attacks, people need advanced cybersecurity systems. Many software helps to prevent cyber-attacks. However, these are not able to early detect suspicious internet threat exchanges. This research used machine learning models in cybersecurity to enhance threat detection. Reducing cyberattacks internet and enhancing data protection; this system makes it possible to browse anywhere through the internet securely. The Kaggle dataset was collected to build technology to detect untrustworthy online threat exchanges early. To obtain better results and accuracy, a few pre-processing approaches were applied. Feature engineering is applied to the dataset to improve the quality of data. Ultimately, the random forest, gradient boosting, XGBoost, and Light GBM were used to achieve our goal. Random forest obtained 96% accuracy, which is the best and helpful to get a good outcome for the social development in the cybersecurity system.

Low enrollment intention threatens the funding pools of rural insurance schemes in developing countries. The purpose of this study is to investigate how social capital enhances the enrollment of health insurance among rural middle-aged and elderly. We propose that social capital directly increases health insurance enrollment, while indirectly influences health insurance through health risk avoidance. We used data from the China Health and Retirement Longitudinal Study (wave 4) dating the year of 2018, instrumental variable estimation was introduced to deal with the endogeneity problem, and the mediation analysis was used to examine the mechanism of social capital on insurance enrollment. The results show that social capital is positively related to social health insurance enrollment, and the relationship between social capital and social health insurance enrollment is mediated by health risk avoidance.

In recent years, how farmers leverage social capital to improve their well-being has become a crucial question in post-poverty alleviation China. This study assessed the impact of ‘linking social capital’ on farmers’ well-being, as mediated by self-efficacy. The study was conducted using data collected from 443 randomly selected farmers from two villages in Guizhou Province, China. The Partial Least Squares Structural Equation Model (PLS-SEM) was employed to analyze the proposed relationships in the study. The results indicate that linking social capital, when mediated by self-efficacy, positively impacted farmers’ well-being. This suggests that policymakers and implementers exercising hierarchical power in social improvement programs in disadvantaged provinces, such as Guizhou, should take full advantage of linking social capital to effectively improve farmers’ well-being. In doing so, the study concludes, they should consider the positive role farmers’ self-efficacy can play in the process.

service-learning activities are effective in higher education programmes. During the COVID-19 period, universities have implemented this methodology and students have improved their social and practical skills. The purpose of this article is to analyse the role of higher education in the process of adapting teaching based on experiences designed for students to serve the community. This research presents the results of a specific service-learning experience of 35 students from the Teamworking programme during the academic years 2020–21 (online) and 2021–22 (face-to-face), in collaboration with the San Juan de Dios Foundation in Madrid, which provides care for people with disabilities. Students evaluated the experience through a quantitative study based on a questionnaire previously developed by Folgueiras (2013), divided into four dimensions. Students also provided some feedback, explaining that this experience changed their perception of people with disabilities, considering the personal value of contributing to social inclusion through service learning. The results show that through the Folgueiras model, students have strengthened their social skills and competences, and through an applied training project that offers the opportunity to build a real relationship through different activities, where learning was at the centre of the interaction between students and young people with disabilities. In conclusion, although the evaluation was positive in terms of the students’ professional and human development, this project requires continuous improvement in the long term, since the subjectivity of human relationships follows a dynamic course with variables that are sensitive to time and individual experience.

The paper reports on the results of research on the institution of public-private partnerships in the field of implementation of state youth policy, particularly through socially important social youth projects, including social-entrepreneurial. The study explores social projects that enjoy the full range of support from all subjects in public-private partnerships: the state represented by public authorities, business structures, non-profit organizations, and youth. The authors highlight that the infrastructure of youth policy in the implementation of social-entrepreneurial youth projects needs to be changed conceptually. There is a need to establish comprehensive creative and professional spaces that shape young people’s personalities and practice a future-oriented model of organizing collaborative social projects.

Considering the role of tourism in promoting sustainable practices in destinations, this study aims to map the scientific literature on footprint calculators in the last three years (2020–2023) with a focus on the tourism context. The method adopted is a scoping review with a qualitative and exploratory approach, using the Scopus database. The originality of this research lies in the study of publications related to footprint calculators with a focus on the tourism sector. Based on the analysis carried out, the main results show that the study of footprint calculators applied to the tourism sector has had little prominence in the indexed research in the Scopus database during the specific period considered for this study. Consequently, the conclusion of the study highlights the marginality of the tourism sector in the discussion of footprint calculators in the last 3 years of scientific publications.