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.

The aim of this research is to determine the incidence of socioeconomic variables in migration flows from the main countries of origin that form part of the international South-North migration corridor, such as Mexico, China, India, and the Philippines, during the 1990–2022 period. The independent variables considered are GDP per capita, unemployment, poverty, higher education, and public health, while the dependent variable is migration flows. An econometric panel data model is implemented. The tests conducted indicate that all variables have an integration order of I (1) and exhibit long-term equilibrium. The econometric models used, Dynamic Ordinary Least Squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS), reveal that unemployment and poverty had the strongest influence on migration flows. In both models, within this international migration corridor, GDP per capita, higher education, and health follow in order of importance.

This study aims to examine and analyze financial statement fraud from the perspective of the hexagon theory using secondary data. The research sample was selected through purposive sampling, consisting of Ministries and Agencies in Indonesia. The research method employing the OLS (ordinary least squares) approach involves testing the model’s suitability through the F-statistical test, evaluating the coefficient of determination by examining, and conducting hypothesis testing using EViews. The findings of this study suggest that pressure and sscapability do not significantly influence financial reporting fraud. In contrast, opportunity, rationalization, arrogance, and collusion positively and significantly impact financial fraud reports. Implementing a whistleblowing system is crucial for ensuring that e-procurement encompasses all elements of government organizations, serving as a means of transparency and accountability to mitigate the occurrence of fraudulent financial reports within government entities, particularly in Ministries and Agencies in Indonesia. The financial audit opinion is not intended to detect fraud but to assess conformity with government accounting standards, the extent of disclosure, compliance with legislation, and the effectiveness of the government's internal control system. This can encourage institutions in other countries to strengthen the financial security of their organizations.

Africa has been fighting against colonialism and Eurocentrism for a long time in an attempt to reverse the regime of oppression and socio-economic marginalization and exploitation, and take back control of its cultural identity and right to self-determination. This adventure requires the recognition and revitalisation of indigenous arts, culture, and law—all of which have been subjugated and ignored during colonial rule. Ironically, the situation has not improved much by the dominating presence of post-independent neo-colonial structures and perpetuated Eurocentric phenomenon that have been ingrained into the socio-cultural and economic fabrics of the African state. This research explores the critical need for integrating science on African indigenous arts, culture, and legal systems, as a way of globalizing as well as revitalizing these elements, towards the ultimate emancipation of the continent from the vestiges of colonialism and Eurocentricism. Relying on the postcolonial, and indigenous knowledge systems theoretical frameworks, the study engages the ethnographic, collaborative and interdisciplinary research approaches, subjecting data obtained to thematic analysis. Underscoring the profound interconnectedness of science, indigenous arts, and cultural heritage, the study argues that combining scientific methods with indigenous African epistemology provides a powerful framework for advancing Africa’s true independence from the protracted legacies of colonialism and Eurocentrism. The research concludes that a holistic integration of these elements therefore, is indispensable for fostering a decolonized and inclusive approach to knowledge production, self-determination and sustainable development, against the background of the rich insights and sustainable practices embedded within the African cultural traditions. Ultimately, the research recommends that embracing and integrating science on indigenous epistemologies can propel Africa towards an emancipated, truly independent, and culturally affirming future, transcending the enduring legacies of colonialism and Eurocentrism.

The objective of this research paper is to investigate potential avenues for value creation in the refined sugar market for domestic use, a market currently facing a critical juncture. The growing concerns about the health impacts of sugar have resulted in a notable decline in demand. Furthermore, changes in European Union regulations have introduced additional operators into the Spanish market, increasing competition and amplifying the need for innovation. This study examines how brands can respond to these challenges by enhancing their value proposition through market segmentation, targeted marketing strategies, and adaptive packaging solutions. To achieve this objective, we have conducted market research, which involved an in-depth interview, and a questionnaire distributed to 402 individuals responsible for household purchases. The findings suggest potential approaches for addressing the needs of consumers with a focus on health and well-being, while simultaneously enhancing the durability of products, thus facilitating greater brand differentiation. Furthermore, the study underscores the pivotal role of public policies and regulatory frameworks in influencing consumer behavior and market dynamics. Policies promoting sugar alternatives, labelling requirements, and packaging innovations have been demonstrated to impact brand strategies and consumer preferences. By aligning with these policy-driven shifts, companies can enhance their positioning in a mature and competitive market. This research contributes to the existing literature on brand value in commodity markets by integrating insights into the impact of regulation and consumer segmentation. Our recommendations emphasize the importance of marketing strategies that are informed by an understanding of the policy context, which not only enhances brand equity but also promotes sustainable growth in the retail sugar industry.

This research conducts a comparative urban analysis of two coastal cities with analogous tourism models situated in distinct geographical regions: Balneário Camboriú in Brazil and Benidorm in Spain. The study delves into two critical urban phenomena impacting the sustainability of tourist cities, utilising social network data to gather insights into economic and urban activities (Google Places) and spatio-temporal patterns of citizen presence (Twitter). The spatial analysis explores the municipal and, to a more detailed extent, the coastal strip extending 500 m inland from the coastline, spanning the entire length of each city to their municipal boundaries. The analysis uncovers both similarities and differences between the two destinations, offering insights that could inform future development strategies aimed at fostering sustainable urban environments in these well-established coastal tourist areas.