Vehicular ad hoc networks (VANET) are also known as intelligent transportation systems. VANET ensures timely and accurate communications between vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) to improve road safety and enhance the efficiency of traffic flow. Due to its open wireless boundary and high mobility, VANET is vulnerable to malicious nodes that could gain access into the network and carry out serious medium access control (MAC) layer threats, such as denial of service (DoS) attacks, data modification attacks, impersonation attacks, Sybil attacks, and replay attacks. This could affect the network security and privacy, causing harm to the information exchange within the network by genuine nodes and increase fatal impacts on the road. Therefore, a novel secure trust-based architecture that utilizes blockchain technology has been proposed to increase security and privacy to mitigate the aforementioned MAC layer attacks. A series of experiment has been conducted using the Veins simulation tool to assess the performance of the proposed solution in the terms of packet delivery ratio (PDR), end-to-end delay, packet loss, transmission overhead, and computational cost.

The web application has become a primary target for cyber criminals by injecting malware especially JavaScript to perform malicious activities for impersonation. Thus, it becomes an imperative to detect such malicious code in real time before any malicious activity is performed. This study proposes an efficient method of detecting previously unknown malicious java scripts using an interceptor at the client side by classifying the key features of the malicious code. Feature subset was obtained by using wrapper method for dimensionality reduction. Supervised machine learning classifiers were used on the dataset for achieving high accuracy. Experimental results show that our method can efficiently classify malicious code from benign code with promising results.

This paper demonstrates a broad exploration of existing authentication and secure communication of unmanned aerial vehicles (UAVs) in a ‘6G network’. We begin with an overview of existing surveys that deal with UAV authentication in 6G and beyond communications, standardization, applications and security. In order to highlight the impact of blockchain and UAV authentication in ‘UAV networks’ in future communication systems, we categorize the groups in this review into two comprehensive groups. The first group, named the Performance Group (PG), comprises the performance-related needs on data rates, latency, reliability and massive connectivity. Meanwhile, the second group, named the Specifications Group (SG), is included in the authentication-related needs on non-reputability, data integrity and audit ability. In the 6G network, with blockchain and UAV authentication, the network decentralization and resource sharing would minimize resource under-utilization thereby facilitating PG targets. Furthermore, through an appropriate selection of blockchain type and consensus algorithms, the SG’s needs of UAV authentication in 6G network applications can also be readily addressed. In this study, the combination of blockchain and UAV authentication in 6G network emergence is reviewed as a detailed review for secure and universal future communication. Finally, we conclude on the critical identification of challenges and future research directions on the subject.

There are continued advances in the internet and communication fields regarding the deployment of 5G-based applications. It is expected that by 2030, 6G applications will emerge as a continued evolution of the mobile network. Blockchain technology is one of the leading supporting technologies predicted to provide a secure and unique network to 6G-enabled devices, transactions, and applications. It is anticipated that the 6G mobile networks will be virtualized, have cloud-based systems, and aim to be the foundation for the Internet of Everything. However, along with the development of communication technologies, threats from malicious parties have become more sophisticated, making security a significant concern for the 6G era in the future. Despite enormous efforts by researchers to improve security and authentication protocols, systems still face novel intrusion and attacks. Recently, multifactor authentication techniques (MFA) have been deployed as potential solutions to attacks in blockchains. The 6G applications and the cellular network have specific vulnerabilities that need to be addressed using blockchain-based MFA technologies. The current paper is a systematic review that discusses the three technologies under consideration; then, several studies are reviewed that discuss MFA techniques in general and use blockchains as potential solutions to future security and authentication issues that may arise for 6G applications.

This study investigate the effectiveness of using Deep Learning (DL) for the classification of planetary nebulae (PNe). It focusses on distinguishing PNe from other types of objects, as well as their morphological classification. We adopted the deep transfer learning approach using three ImageNet pre-trained algorithms. This study was conducted using images from the Hong Kong/Australian Astronomical Observatory/Strasbourg Observatory H-alpha Planetary Nebula research platform database (HASH DB) and the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS). We found that the algorithm has high success in distinguishing True PNe from other types of objects even without any parameter tuning. The Matthews correlation coefficient is 0.9. Our analysis shows that DenseNet201 is the most effective DL algorithm. For the morphological classification, we found for three classes, Bipolar, Elliptical and Round, half of objects are correctly classified. Further improvement may require more data and/or training. We discuss the trade-offs and potential avenues for future work and conclude that deep transfer learning can be utilized to classify wide-field astronomical images.

University-industry research collaboration (UIRC) is a major source for research, innovations and sustainable economic growth. Despite the extensive evidence on the importance of such collaboration in developed and developing countries, literature related to the strengthening of this collaboration, along with its innovation performance, is still scarce. Scholars believe that the impact of exchanging information has a vigorous influence on researcher’s innovative activities as well as research and innovations. Moreover, to flatten the flow of exchanging information between researchers, it is mandatory to refurbish human capital in conjunction with intellectual capital, along with their reinforcing factors i.e., communication and networking, respectively. In this paper, we evaluate the influence of human capital and intellectual capital along with their corresponding reinforcing factors on exchanging information using the system thinking method. Evidence from UIRC in Malaysia provides empirical corroboration that intellectual capital along with its reinforcing factors has a significant influence on exchanging information. Thus, the findings of this research suggest that intensifying the capabilities of intellectual capital with a reinforcing effect can sustain the circulation of exchanging information.