PurposeDue to the lack of awareness and poor cybersecurity practices that pose cyber threats during COVID-19 time, this research aims to explore user's attitude toward engaging in proactive cybersecurity awareness behavior.Design/methodology/approachBased on the theory of planned behavior, the relationship between multiple factors and their influence on the attitude is explored. A survey-based approach was utilized to collect responses and a model was proposed and tested on 229 respondents from the University of Petra-Jordan.FindingsThe attitude was significantly influenced by peers' influence and the individuals' cybersecurity threats awareness, especially threats that emerged during the COVID-19 time.Research limitations/implicationsThe research benefits decision makers in educational institutions who intend to develop cybersecurity awareness programs and helps them to assess user cybersecurity background weaknesses.Originality/valueThe research is the first to explore users' knowledge dimensions including organizational, information systems and social media as well as peers' influence on cybersecurity awareness. Also, it sheds light on the users’ perception of major cybersecurity hazards in COVID-19 time.
The location-aided routing scheme 1 (LAR-1) and probabilistic algorithms are combined together into a new algorithm for route discovery in mobile ad hoc networks (MANETs) called LAR-1P. Simulation results demonstrated that the LAR-1P algorithm reduces the number of retransmissions as compared to LAR-1 without sacrificing network reachability. Furthermore, on a sub-network (zone) scale, the algorithm provides an excellent performance in high-density zones, while in low-density zones; it preserves the performance of LAR-1. This paper provides a detailed analysis of the performance of the LAR-1P algorithm through various simulations, where the actual numerical values for the number of retransmissions and reachability in high- and low-density zones were computed to demonstrate the effectiveness and significance of the algorithm and how it provides better performance than LAR-1 in high-density zones. In addition, the effect of the total number of nodes on the average network performance is also investigated.
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