Digital transformation in energy sector organizations has huge benefits but also exposes them to cybersecurity challenges. In this paper, we carried out a systematic literature review on cybersecurity challenges and issues in the energy domain. Energy-associated assets are very critical for any nation and cyber-attacks on these critical infrastructures can result in strategic, financial, and human losses. We investigated research papers published between 2019 and 2024 and categorized our work into three domains: oil and gas sector, the electricity sector, and the nuclear energy sector. Our study highlights that there is a need for more research in this important area to improve the security of critical infrastructures in the energy sector. We have outlined research directions for the scientific community to further strengthen the body of knowledge. This work is important for researchers to identify key areas to explore as well as for policymakers in energy sector organizations to improve their security operations by understanding the associated implications of cybersecurity.

Digital transformation of businesses has seen tremendous growth recently, moreover, COVID-19 has increased online shopping. However, it is important for businesses that customers’ online shopping experience is secure and joyful. In this paper, customers’ security perception regarding some leading mobile commerce applications in Saudi Arabia is explored. Our survey questions focused on three aspects, namely: Consumer rating, trustworthiness, and credit card security. The results highlight that consumers perceive that mobile commerce applications in Saudi Arabia need further improvement in security. In this work, a model to improve customers’ security perception in Saudi Arabia is presented. This model can be generalized to other geographical regions as well. The model outlines different actions for practitioners and policymakers that help in improving security infrastructure, authentication mechanisms, and trustworthiness.

Program outcome assessment is a complex process that demands careful planning and resources in order to accurately assess higher-order thinking skills. A well-defined assessment approach provides detailed insights into program weaknesses and leads to continuous improvement. Whereas a poor assessment approach does not reflect the underlying weaknesses and may result in a useless effort. Furthermore, each accreditation body may have a different recommended outcome measurement approach. As a result, academic institutions may make adhoc choices just to satisfy accreditation requirements rather than designing a sustainable measurement approach. On the other hand, the magnitude of huge tasks for satisfying multiple accreditation bodies results in fatigue and mental stress for academic staff. ABET is a well-known international program accreditation body, and NCAAA is a local accreditation body for academic programs in the Kingdom of Saudi Arabia. In this paper, we have documented that how a sustainable outcome measurement mechanism can be designed to satisfy both ABET and NCAAA requirements. The core contribution of this paper is relevant specifically for academic programs in the Kingdom striving to meet both ABET and NCAAA requirements and is also relevant for all education programs to design an appropriate program assessment approach to ensure a sustainable process to foster better learning among students.

In medical treatments and care, medical health is a critical area that requires immediate attention of and can benefit greatly from current day technology. Advancements in IOT development is transforming all facets of our everyday lives and it’s our belief that it can play an important role in mental healthcare too. This paper proposes a human centered model which incorporates the use of the latest IOT wearable technologies along with a fully encrypted cloud computing algorithm that can potentially help in improving the identification and treatment of mental healthcare patients by integrating suggested measures and means of data acquisition, collection, transmission, processing and protection. If done right, with further detailed research that focuses on mental health, we can expect to see significant improvements in treatment and diagnosis methods for patient suffering from mental conditions in the very near future. Our emphasis is on creating a human centered model that can be converted into an interactive app with responsive features that can suggest different treatment measures based on the information collected from the Big Data gathered through the IOT sources utilized and depending on the patient’s condition with utmost security protection of the confidential data.

Government websites are the easy sources of getting access to the services offered by governmental organizations. These websites provide manifold benefits to their users i.e. efficiency of use, cost decline, effective communication between citizens and government, delivery of different service, transparency and time saving. However, users cannot get full benefit out of these services if the e-government websites are not interactive and user friendly. Keeping this view into consideration, study investigated the usability concerns of the e-government websites in Saudi Arabia. Cognitive walk-through is selected as the implication method to figure out usability related traits by the real users of the interfaces. Findings from the study showed that these websites are partially usable for the users, as they lack some of the major concerns of the usability. Evaluation results showed the clear picture of the usability features of the selected websites of Saudi Arabia both in positive and negative ways. Furthermore, recommendations are given to improve overall quality of these websites.

Modern human life is heavily dependent on computing systems and one of the core components affecting the performance of these systems is underlying operating system. Operating systems need to be upgraded to match the needs of modern-day systems relying on Internet of Things, Fog computing and Mobile based applications. The scheduling algorithm of the operating system dictates that how the resources will be allocated to the processes and the Round Robin algorithm (RR) has been widely used for it. The intent of this study is to ameliorate RR scheduling algorithm to optimize task scheduling. We have carried out an experimental study where we have developed four variations of RR, each algorithm considers three-time quanta and the performance of these variations was compared with the RR algorithm, and results highlighted that these variations performed better than conventional RR algorithm. In the future, we intend to develop an automated scheduler that can determine optimal algorithm based on the current set of processes and will allocate time quantum to the processes intelligently at the run time. This way the task performance of modern-day systems can be improved to make them more efficient.