Social Engineering (SE) Attacks against information systems continue to pose a potentially devastating impact. Security information systems are becoming increasingly significant as the number of SE incidents rapidly increased and became more aggressive than before. The World Wide Web (WWW) has evolved for information exchange and knowledge-sharing. It enables the sharing of information in a timely, effective, and transparent manner. Identity theft and identity misuse are two sides of cybercrime in which hackers and fraudulent users collect sensitive information from current legal users in order to perform fraud or deceit for financial gain. Malicious links are used as phishing methods, in which malicious links are planted beneath legitimate-looking links. As the number of web pages grows, the number of malicious web pages and the attacks of such become more complex. In this paper, we provide a method for identifying malicious web pages using a crawling and classification approach that helps to support the automatic discovery of the malicious links. The proposed approach can successfully complete the crawling session even if the page requires partial page refreshment and authentication credentials. The evaluation of the proposed approach shows a higher accuracy compared to an existing approach with an overall accuracy of 72% in three custom applications. Moreover, the proposed approach will calculate the significance and the impact severances of each link on the website and it better differentiates malicious web pages and normal links. The results of the proposed approach will also help in providing a set of recommendations which can increase the awareness level of the end-users, website administrators on how to better deal with these types of SE attacks.

The aim of this study is twofold. First, to explore the effect of smart human resources (HR) 4.0 practices on employee effectiveness. Second, to investigate the mediating role of employee job satisfaction in the relationship between these two latent variables. Distributing a questionnaire to gather data from a sample of HR managers and employees in Ministry of Digital Economy and Entrepreneurship, the results point out that smart HR 4.0 practices as a whole construct represent a significant predictor of employee job effectiveness as measured by employee performance based on their personal, social, methodological, and technical skills. As well, the results revealed that smart HR 4.0 embodies a significant predictor of employee job satisfaction. The results found a significant effect of the latter on employee job effectiveness, a significant mediating role of employee job satisfaction was established. The study provides a theoretical basis for further studies on such effects as well as an empirical ground from which companies could start to boost employee satisfaction and effectiveness through smart HR 4.0 technologies.

It is critical to safeguard confidential data, especially secret and private messages. This study introduces a novel data cryptography approach. The new approach will be capable of encrypting and decrypting any communication size. The suggested approach will use a sophisticated private key with a convoluted structure. The private key will have 5 components with a double data type to prevent guessing or hacking. The confidential data will produce two secret keys, the first of which will be taken from the image key. These keys will be vulnerable to slight changes in private key information. To maximize the approach's efficiency, the suggested method will deal with lengthy messages by splitting them into chunks. On the other hand, the chaotic logistic map model will be used to create the second key. The suggested technique will be implemented, and several sorts of analysis (sensitivity, quality, security, and speed analysis) will be undertaken to demonstrate the benefits of the proposed method. The quality metrics MSE, PSNR, and CC will be computed to validate the suggested method's quality. To illustrate the efficiency of the proposed technique, encryption and decryption times will be measured, and cryptography throughputs will be determined. Various PKs will be tried throughout the decryption process to demonstrate how sensitive the produced outputs are to changes in the private key. The suggested approach will be tested, and the results will be compared to the results of existing methods to demonstrate the improvement offered by the proposed method.

Peru is a country with a complex geography. Moreover, it lacks minimal safe roads, higher in Andean and jungle territories. Depending on the classification they might receive, the num-ber of kilometers without pavement can reach up to 80%. Such a rate is alarming, consider-ing that internationally the United Nations promotes actions for road security since road ac-cidents are among the most common causes of death causes in the world. Then, employing data from Sutran, the current research has analyzed how the severity of accidents can affect road administration in Peru roads in 2021. Hence, the multinomial logistic regression was employed due to the nature of the data. It was found that regional routes had a higher risk than national roads when estimating the probability of having many dead and injured people because of a road accident.

The development of wearable technology opens the potential for its use in various sectors, one of which is the use of smartwatches in the sports sector. This paper examines soccer players' behavior's impact on using smartwatches as a training monitoring tool. This study uses a quantitative approach involving as many as 128 soccer players to complete a research questionnaire with face to face (offline). SEM-PLS is used as an analytical method to test the proposed inferential model. As a result, research shows that social influences, relative advantages, and enjoyment impact the use of smartwatches during training and daily use by soccer players.

The rapid increase in social media users in Indonesia has caused organic black rice (OBR) to be traded online via social commerce (s-commerce). OBR is an environmentally friendly functional food that meets the requirements for sustainable agricultural products. Unfortunately, in Indonesia the demand is still low, so some producers are reluctant to continue the OBR business. Therefore, it is important to study consumer satisfaction. Previous studies have primarily focused on satisfaction with choices and results of the decision process, not satisfaction with the decision process. Satisfaction in the perspective of the decision process has not been widely studied. This paper aims to identify the dominant factors that influence satisfaction with the online OBR purchase decision process via s-commerce. The research design is quantitative with a survey technique of 200 online consumers drawn by stratified random and convenience sampling. Data analysis using Exploratory Factor Analysis and Path Analysis. The results showed that the dominant factors were security in purchasing decisions, Instagram and other social media, friends, satisfaction with the results, Internet, references of friends and family as well as consideration of product taste and aroma, attractiveness, and disease treatment. These eight dominant factors can be used as important considerations in online OBR business through s-commerce.

Blockchain technology adoption among the businesses has become a new updated technological improvement and calls all businesses to care with it. This research aims to address its effect with project management information systems with a possible moderation effect of the value creation gained of this factor. The study used a quantitative research method to meet its objective and collected the data from Jordanian e-commerce enterprises with a total of 320 participants. PLS-SEM technique was used to perform the key analyses. The results found a significant effect of all hypothesized research assumptions and a significant moderating effect of value creation on the respective effect of study’s variables. The findings also expanded the current understanding and application of this technology and showed some implications and applicable insights that supported the existing literature and evidence in this field. The study would contribute to cover the limited research works and knowledge gaps with a suggestion to integrate this technology and application within different contextual settings.

Phishing websites are characterized by distinguished visual, address, domain, and embedded features, which identify and defend such threats. Yet, phishing website detection is challenged by overlapping these features with legitimate websites’ features. As the inter-class variance between legitimate and phishing websites becomes low, commonly utilized machine learning algorithms suffer from low performance in overlapping feature cases. Alternatively, ensemble learning that combines multiple predictions intending to address low inter-class variations in the classified data improves the performance in such cases. Ensemble learning utilizes multiple classifiers of similar or different types with multiple deviations of the training data. This paper develops a framework based on random forest ensemble techniques. The limitations of the random forest are the inability to capture the high correlation between features and their join dependency on the label. The random forest is combined with k-means clustering to capture the feature correlation. The framework is evaluated for phishing detection with a dataset of 5000 samples. The results showed the proposed framework over-performed the random forest classifier, all other ensemble classifiers, and the conventional classification algorithms. The proposed framework achieved an accuracy of 98.64%, precision of 0.986, recall of 0.987, and F-measure of 0.986.

Digital governance, institutional development and public higher education in Huancayo-Perú in the new situation where remote activities are prioritized, the use of information technologies has increased in the different activities of organizations, allowing them to provide adequate services in an efficient way. The research seeks to establish the relationship between digital governance and institutional development in public higher education in Huancayo - Perú. Basic research with a quantitative approach and correlational level with a sample of 828 people made up of teaching staff, administrative staff and students who interact with the administrative activities of the UNCP. The data analysis and modeling was performed through structural equations based on PLS. As a result of the research, a value of 0.815 was obtained in Spearman's Rho and a significance level of .000, which indicates a high positive relationship, also the general hypothesis that establishes that there is a significant relationship between digital governance and institutional development is accepted.

This study begins with a literature review to observe current problems surrounding vehicle service centers and the use of the ARIMA method to resolve similar cases. Researchers then conduct the observation process by collecting user needs through surveys and questionnaires. Next, researchers use the Scrum methodology to develop a web-based application enriched with the ARIMA method. Afterward, researchers obtain user feedback using surveys and questionnaires to evaluate the user experience towards the application. Conclusively, based on the results of the questionnaires, the average respondent believes that the web-based application can simplify respondents in making vehicle service reservations with a score of 8.85 out of 10. In addition, the average respondent believes that the web-based application can assist respondents in planning vehicle service. They visit with shorter queue times through a crowded time prediction system on a web-based reservation application with the ARIMA model with a value of 8.9 out of 10.