Ad hoc networks, known as infrastructure-less networks, are composed of mobile nodes that connect without a centralized system controlling them. These networks have a wide range of potential applications, including emergency response, events, military operations, wireless access, and intelligent transportation. They can take on various forms, such as wireless sensor networks, wireless mesh networks, and mobile ad hoc networks. Because users in these networks can move around at any time, routing protocols must adapt to the constantly changing network layout. However, these networks are also susceptible to various security threats, including DDoS attacks. This paper aims to analyze the performance and impact of security attacks on the performance of reactive and proactive routing protocols in CBR connection patterns with different pause times. The analysis is provided in metrics such as throughput, packet loss, end-to-end delay, and load. The simulation results show that, on average, the OPNET Modeler simulator analyzed the performance results under DDoS attacks under voice and video traffic conditions. Furthermore, the paper explores the use of Honeypot intelligent agents as a solution to increase security by creating a dummy node to fool DDoS attackers. The results show that the OLSR protocol is most affected by DDoS attacks in terms of quality-of-service metrics such as packet loss, throughput, end-to-end delay, and load. The number of responses to the honeypot solutions differs for each protocol.

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.

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.

The online markets have been growing during the last near years, and many businesses have generated customer satisfaction and loyalty by developing their marketing activities. The main aim of this study is to review the related body of the literature to develop a thorough conceptual research framework including e-marketing in order to determine the respective antecedent factors of customer satisfaction and loyalty. Another study aim is examining the mediating role of the perceived value on the interrelationships between e-marketing, customer satisfaction and loyalty. Through a questionnaire survey, the study collected the data from various online shoppers in Jordan with about 482 participants. The study results indicated that e-marketing had a significant effect on customer satisfaction but did not generate customer loyalty, and the customer satisfaction had a significant effect on customer loyalty. Another key result is the perceived value mediated the relations between e-marketing and both customer satisfaction and customer loyalty. The study's respective implications offer new insights in marketing literature and conclude that the successful marketing activities should focus on the perceived value that is felt by the customers.

This study came to examine the impact of Digital transformation on sustainable performance. The research population consisted of employees of Industrial companies listed in Amman stock exchange that is 23 companies. Because of the difficulty of collecting data using a complete census, a random sample of 530 employees was determined. 397 responses were used for the purposes of the statistical analysis of this research. In order to find the impact of digital transformation on sustainable performance, the structural equation modeling (SEM) technique was used. Research results show that digital transformation dimensions had a positive impact on sustainable performance. Big data had the greatest impact. Accordingly, the researchers recommend Industrial companies invest more in manufacturing modern technologies, represented by Digital transformation technologies that give companies the ability to provide high-quality performance and prepare an infrastructure to operate these technologies.

Blockchain technology is one of the crypto-currency technologies that has received a lot of attention. It has also found use in various applications, including the Internet of Things (IoT) and Cloud computing. Nonetheless, Blockchain has a significant scalability issue, restricting its ability to support services with various transactions. On the other hand, cloud computing is the on-demand availability of shared computer system resources, although issues now beset it in automation, processes, management, policies, and human aspects. Combining cloud computing and blockchain technology into a single system can improve network control, task scheduling, data integrity, resource management, pricing, fair payment, and resource allocation. In this article, we offered a comprehensive and up-to-date survey of cloud computing and Blockchain integration, a critical service for business applications due to the benefits of privacy, security, and service support. The lack of a comprehensive assessment examining the significance of BaaS platforms used in cloud computing prompted this review. We focus on the various BaaS tools that are currently in use. This report also examines the most common BaaS platforms incorporating Blockchain as a cloud service, such as Alibaba, Oracle, Azure, Amazon, and IBM. Furthermore, this research highlighted some major technological issues associated with merging Blockchain with cloud computing.

The purpose of the paper is to select the mediating role of information integration between cloud computing and productivity. The research sample comprised 320 employees. Survey was utilized to gauge the cloud computing impact on productivity and information integration. 281 questionnaires returned for statistical analysis, adopting the quantitative approach. The study's findings indicated that productivity standards, applying information integration, and cloud computing usage were all highly prevalent. In addition, there was an impact for cloud computing on productivity and information integration. Recommendations for study were discussed.