Trust and reputation management for securing collaboration in 5G access networks: the road ahead

Trust represents the belief or perception of an entity, such as a mobile device or a node, in the extent to which future actions and reactions are appropriate in a collaborative relationship. Reputation represents the network-wide belief or perception of the trustworthiness of an entity. Each entity computes and assigns a trust or reputation value, which increases and decreases with the appropriateness of actions and reactions, to another entity in order to ensure a healthy collaborative relationship. Trust and reputation management (TRM) has been investigated to improve the security of traditional networks, particularly the access networks. In 5G, the access networks are multi-hop networks formed by entities which may not be trustable, and so such networks are prone to attacks, such as Sybil and crude attacks. TRM addresses such attacks to enhance the overall network performance, including reliability, scalability, and stability. Nevertheless, the investigation of TRM in 5G, which is the next-generation wireless networks, is still at its infancy. TRM must cater for the characteristics of 5G. Firstly, ultra-densification due to the exponential growth of mobile users and data traffic. Secondly, high heterogeneity due to the different characteristics of mobile users, such as different transmission characteristics (e.g., different transmission power) and different user equipment (e.g., laptops and smartphones). Thirdly, high variability due to the dynamicity of the entities’ behaviors and operating environment. TRM must also cater for the core features of 5G (e.g., millimeter wave transmission, and device-to-device communication) and the core technologies of 5G (e.g., massive MIMO and beamforming, and network virtualization). In this paper, a review of TRM schemes in 5G and traditional networks, which can be leveraged to 5G, is presented. We also provide an insight on some of the important open issues and vulnerabilities in 5G networks that can be resolved using a TRM framework

Evaluation of Student and Staff Perceptions on L&T Models Across Multiple Disciplines

Moving towards Education 4.0, there has been a gradual shift in learning and teaching (L&T) practices worldwide towards active and deep learning (Gardiner, 2015). With technological advancements, different models of learning and teaching utilising digital mediums have evolved, alongside with frameworks to support transitions into enhanced blended learning (Adekola, Dale, & Gardiner, 2017). It was proposed that the students’ learning needs and expectations must be considered in the L&T pedagogy. In Ithaca S+R and the Univer¬sity System of Maryland, parallel comparisons of traditional versus blended courses were conducted (Griffiths, Chingos, Mulhern, & Spies, 2014). In this study, students on the blended courses performed slightly better or as well as those on the traditional courses but enjoyed the course less. At the University of Glasgow Singapore, L&T with different modes of blended instruction was explored. Four courses in Computing Science, Nursing, Mechatronics and Civil Engineering, which were hosted on different learning management systems, FutureLearn, Moodle and xSiTe, were considered. Across these courses, varying lesson plans and proportion of digital versus Face-to-face (F2F) interactions were provided. Lesson plans ranged from supplementary learning with videos to active and blended learning. Two surveys were developed to evaluate the staffs’ and students’ experiences. These included MCQs with a Likert-scale, as well as open ended questions. In this study, quantitative data was imported into Excel for visualisation, while qualitative data was subjected to categorisation and analysis (Braun & Clarke, 2006). Results were collated from at least fifty respondents in each course. The evaluation study for the students was developed on the following areas: (1)Accessibility; (2)Acceptance Levels; (3)Learner’s Gain; (4)Learner’s Experience; (5)Learner’s Perception; (6)Viewing Duration; (7)Repeated Viewing; (8)Useful to Learning; (9)Higher Level Learning; and (10)Acceptance levels on proportion of Videos versus F2F interactions. Similar questions were posed to lecturers. Some of the key findings are as follows: (i) All four lecturers believe that the videos helped to raise the level of classroom discussion and channelled F2F consultation time to enhance the L&T gain for students. (ii) Most learners used a laptop for video viewing. This is closely followed by the smartphone, especially for Nursing. (iii) More than 93% of the learners believe that videos are helpful in their learning. (iv) Concept reinforcement was ranked to be most important approach for successful learning outcomes. Students also appreciate foundational materials and content to evoke active learning and critical thinking. (v) Over 78% of the students felt that they had to repeat the viewing of videos to grasp the concepts. (vi) Across all disciplines, more than 88% of the students felt that videos are useful to learning. Above 79% felt that they are learning at a higher level. (vii) Above 81% of the students are comfortable to engage in blended learning and felt that the optimal proportion of F2F consultation versus video time would be between 40% to 60%. In conclusion, it is evident that students are generally comfortable to engage in blended learning, if a good balance of digital and F2F interaction is provided. Students enjoy learning at their own pace and time. Many of the students felt that the digital content enabled them to review their learning and reinforce their understanding. Improvement in summative assessment scores is also demonstrated, where blended learning is offered to students. This project has provided the necessary guidance needed to develop successful courses for active and blended learning and demonstrates L&T examples with different pedagogical approaches. The results will be studied for future course development and lesson planning across all joint SIT-Glasgow degree programmes

Learners’ differences in blended learner-centric approach for a common programming subject

As the number of students entering higher education increases with a growing diversity of background, educators of programming courses face increasing challenges. Different teaching pedagogies need to be explored for students with different background knowledge. Some students find programming courses difficult to understand and practice. It may lead to de-motivation and disengagement in learning process with consequential impact on their grades. Addressing these issues demands approaches for effective teaching programming courses to multidisciplinary cohorts. This article investigates how computing science (CS) and engineering cohorts respond differently to teaching approaches in a common module, Fundamentals of Programming. Both traditional teacher-centric teaching and a blended learner-centric approach have been explored in a diverse group of students. The blended learner-centric approach combines classroom teaching and self-paced blended learning using work examples videos method. These two teaching approaches have been evaluated in Academic Year 2019/2020. It can be seen from the evaluation results of 92 CS and 150 Engineering students who participate in this research that the performance is improved by about 5% through blended learner-centric approach. It is further observed that quantitatively the performance gap between CS and Engineering students has been reduced. Questionnaire survey has also been conducted with 54 CS and 89 Engineering students being responded. The learners’ perceptions of the blended learner-centric approach have also been compared between these two cohorts

Comparing the effectiveness of bivalent and monovalent COVID-19 vaccines against COVID-19 infection during the winter season of 2022-2023: A real-world retrospective observational matched cohort study in the Republic of Korea

Objectives: To compare the effectiveness of bivalent and monovalent COVID-19 vaccines throughout the 2022-2023 winter season based on real-world data. Methods: This retrospective observational matched cohort study used the national vaccination program and a surveillance dataset from the Republic of Korea, and included adults aged >18 years who received bivalent or monovalent COVID-19 vaccines between October 11, 2022, and December 17, 2022. Cox proportional hazard models were used to estimate the hazard ratio for COVID-19 infection between the groups. Results: We included 29,245 matched individuals in the bivalent and monovalent vaccine groups, respectively. The bivalent vaccine recipients showed 12.2% (95% confidence interval [CI] 6.5-17.7%) additional protection against COVID-19 infection compared with the monovalent vaccine recipients. The additional protection provided by bivalent vaccines was significantly higher among residents of long-term care facilities (39.4%, 95% CI 21.6-53.1%). Maximum additional protection was observed 3 to 4 months after completing the vaccination (17.6%, 95% CI 6.6-27.3%). Conclusion: Bivalent COVID-19 vaccines showed significantly better protection against infection than monovalent vaccines among adults during the 2022-2023 winter season. Our results highlight that immunization programs with bivalent vaccines comprising recent variants can be an effective measure to prepare for seasonal COVID-19 circulation