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.

This study aims to examine the role of automotive industry development in the regional growth of Hungarian counties. Through word frequency analysis, the counties were grouped, and their unique characteristics were highlighted. Some counties already play a prominent role in the domestic automotive industry hosting established Original Equipment Manufacturers (OEMs), a significant number of automotive suppliers and high R&D and innovation potential. Another group includes counties that currently lack a significant automotive industry and did not identify it as a key focus area for future development. Additionally, an intermediate group has also emerged, including counties where the automotive industry is either in its early stages of investment, or such development is prioritized in regional planning documents. The study details the direction of automotive development in counties where the industry plays a significant role, focusing on labor market characteristics and human resource development. The findings have significant implications for the future of the automotive industry in these counties, underlining the urgent and immediate need for well-managed and well-established human resource development and ensuring effective partnership to realize its full potential in the automotive industry.

Air cargo transportation accounts for less than 1% of the global trade volume, yet it represents approximately 35% of the total value of goods transported, highlighting its strategic importance in trade and economic development. This study investigates the relationship between domestic air cargo transport in Brazil and key macroeconomic variables, focusing on how regional economic dynamism, logistical infrastructure, and population density impact the country’s development. Using a panel data regression model covering the period from 2000 to 2020, the study analyzes the evolution of air cargo transportation and its role in redistributing economic growth across Brazil’s regions. The findings emphasize the key factors influencing the air cargo sector and demonstrate how these factors can be leveraged to optimize public policies and business strategies. This research provides valuable insights into the relevance of air cargo transportation for regional and national development, particularly in emerging economies like Brazil, offering guidance for the formulation of strategies that promote balanced economic growth across regions.

This study proposes a fuzzy analytic hierarchy process (FAHP) method to support strategic decision-makers in choosing a project management research agenda. The analytical hierarchy process (AHP) model is the basic tool used in this study. It is a mathematical tool for evaluating decisions with multiple alternatives by decomposing them into successive levels according to their degree of importance. The Sustainable Development Goals (SDG) oriented theme of project management was chosen from among four themes that emerged from a strategic monitoring study. The FAHP method is an effective decision-making tool for multiple aspects of project management. It eliminates subjectivity and produces decisions based on consistent judgment.

The use of firearms, their frequency, and legitimacy through self-defence and extreme necessity are socially relevant in Czechia and Slovakia. Legal firearm ownership for defence purposes impacts overall social security, influenced by factors like firearm legislation, cultural traditions, legal awareness, and violent crime rates. Understanding this issue requires considering subjective interpretations, even among security experts. This paper explores the theoretical foundations of self-defence and extreme necessity from criminal law, alongside practical implications supported by police statistics on violent crimes involving firearms in Czechia and Slovakia. It also includes a comparison with selected EU countries. The authors’ research uses a questionnaire to assess attitudes towards choosing defensive firearms, preparation for firearms licensure, and potential support for state security forces. The findings provide insights into legal firearm owners’ behaviours and attitudes toward defence and security. The study aims to contribute to a deeper understanding of firearm use for self-defence, correlating training, weapon preferences, and willingness to enhance state security.

“This paper’s purpose l is to determine whether certain firm-specific factors have an influence on the catering theory of dividend in the MENA region.” The catering theory of dividend related to the dividend policy by the different companies used in our paper to explain the decision by managers. The sample includes 600 non-financial firms listed stocks in the Stock Exchange of 6 countries from MENA region during the years 2010–2019. Catering theory explains why managers initiate (continue) to distribute dividends. A high dividend premium encourages managers to increase the level of dividend payment and explains why firms pay dividends or do not pay them thereafter. Investors should increase their demand for dividends to push managers to comply. Investors show their preference for dividend to self control, satisfaction and increase their profit. “This could be the catering incentive of the firm to decide to pay dividends”. Even although the result Investor preference for dividend is explained by different factors related to the firms characteristics from each firms is different from markets, it can be the evidence supporting the catering theory of dividend, not only in well-developed markets, but also in emerging markets such as our country.