Pharmacy education in Saudi Arabia: A vision of the future

Background: Pharmacy education in developing countries faces many challenges. An assessment of the challenges and opportunities for the future of pharmacy education in Saudi Arabia has not been conducted. Objectives: The purpose of the study was to ascertain the views and opinions of pharmacy education stakeholders regarding the current issues challenging pharmacy education, and to discuss the future of pharmacy education in Saudi Arabia. Methods: A total of 48 participants attended a one-day meeting in October 2011, designed especially for the purpose of this study. The participants were divided into six round-table discussion sessions with eight persons in each group. Six major themes were explored in these sessions, including the need to improve pharmacy education, program educational outcomes, adoption of an integrated curriculum, the use of advanced teaching methodologies, the need to review assessment methods, and challenges and opportunities to improve pharmacy experiential training. The round-table discussion sessions were videotaped and transcribed verbatim and analyzed by two independent researchers. Results: Participants agreed that pharmacy education in the country needs improvement. Participants agreed on the need for clear, measureable, and national educational outcomes for pharmacy programs in the Kingdom. Participants raised the importance of collaboration between faculty members and departments to design and implement an integrated curriculum. They also emphasized the use of new teaching methodologies focusing on student self-learning and active learning. Assessments were discussed with a focus on the use of new tools, confidentiality of examinations, and providing feedback to students. Several points were raised regarding the opportunities to improve pharmacy experiential training, including the need for more experiential sites and qualified preceptors, addressing variations in training quality between experiential sites, the need for accreditation of experiential sites, and the use of technology to track experiential activities and assessments. Conclusion: Several challenges for improving pharmacy education in Saudi Arabia were discussed by stakeholders. To tackle these challenges facing most pharmacy schools in the Kingdom, national efforts need to be considered by involving all stakeholders

Industrial control systems security validation based on MITRE adversarial tactics, techniques, and common knowledge framework

Industrial Control Systems (ICSs) have become the cornerstone of critical sectors like energy, transportation, and manufacturing. However, the burgeoning interconnectivity of ICSs has also introduced heightened risks from cyber threats. The urgency for robust ICS security validation has never been more pronounced. This paper provides an in-depth exploration of using the MITRE ATT&CK (Adversarial Tactics, Techniques, and Common Knowledge) framework to validate ICS security. Although originally conceived for enterprise Information Technology (IT), the MITRE ATT&CK framework’s adaptability makes it uniquely suited to address ICS-specific security challenges, offering a methodological approach to identifying vulnerabilities and bolstering defence mechanisms. By zeroing in on two pivotal attack scenarios within ICSs and harnessing a suite of security tools, this research identifies potential weak points and proposes solutions to rectify them. Delving into Indicators of Compromise (IOCs), investigating suitable tools, and capturing indicators, this study serves as a critical resource for organisations aiming to fortify their ICS security. Through this lens, we offer tangible recommendations and insights, pushing the envelope in the domain of ICS security validation

DDoS cyber-incident detection in smart grids

The smart grid (SG) offers potential benefits for utilities, electric generators, and customers alike. However, the prevalence of cyber-attacks targeting the SG emphasizes its dark side. In particular, distributed denial-of-service (DDoS) attacks can affect the communication of different devices, interrupting the SG’s operation. This could have profound implications for the power system, including area blackouts. The problem is that few operational technology tools provide reflective DDoS protection. Furthermore, such tools often fail to classify the types of attacks that have occurred. Defensive capabilities are necessary to identify the footprints of attacks in a timely manner, as they occur, and to make these systems sustainable for delivery of the services as expected. To meet this need for defensive capabilities, we developed a situational awareness tool to detect system compromise by monitoring the indicators of compromise (IOCs) of amplification DDoS attacks. We achieved this aim by finding IOCs and exploring attack footprints to understand the nature of such attacks and their cyber behavior. Finally, an evaluation of our approach against a real dataset of DDoS attack instances indicated that our tool can distinguish and detect different types of amplification DDoS attacks

A transfer learning-based feature reduction method to improve classification accuracy

The need for efficient data use grows in machine learning algorithm for dataset with larger feature sets. Feature selection is the process of selecting minimum set of features that fully represent the learning problem. Transfer learning can motivate in scenario where we train model with the common problem and use it to identify important features needed to build model for target problem. In this thesis, we propose transfer learning algorithm combined with or without suggested features from experts, to learn from the source dataset and recognize important feature sets needed to train models in target dataset. Also, we compared this algorithm with classical machine learning algorithm with or without using the suggested features recommended by the experts. In series of experiment, it shows that our method is adequate to find the minimum feature sets which also outperformed then using only the suggested features by the experts. Furthermore, it also shows that the subsequent reduce in number of features in transfer learning method have better or almost same performance then using all the features of the dataset. We performed our experiments using heart disease, readmission dataset and BMI dataset

Social and Economic Factors that Influence Health Outcomes in Family Medicine

Over the last twenty years, the social determinants of health (SDOH) have gained more and more attention in the public health community. SDOH are non-medical elements that may be significantly impacted by social policies and have an impact on health. The increasing variety that exists within our societies makes it absolutely necessary for us to incorporate into undergraduate medical education social determinants of health such as racial factors, financial instability, partner violence, insufficient accessibility to transportation, and inadequate social supports, as well as the crucial role of health education.  Nonetheless, a growing body of research indicates that a variety of health outcomes are fundamentally caused by socioeconomic variables including wealth, income, and education together. In this review we highlight the influence of socio-economic factors on health outcomes, approaches to incorporate social determinants of health in family medicine practice, and we also talk about challenges and solutions in addressing social determinants in family medicine. The objective of this research was to assess the impact of social determinants of health on family medicine practice in which socioeconomic determinants of health might have an effect on health outcomes and healthcare delivery within the context of a family medicine clinical environment

Understanding indicators of compromise against cyber-attacks in industrial control systems: a security perspective

Numerous sophisticated and nation-state attacks on Industrial Control Systems (ICSs) have increased in recent years, exemplified by Stuxnet and Ukrainian Power Grid. Measures to be taken post-incident are crucial to reduce damage, restore control, and identify attack actors involved. By monitoring Indicators of Compromise (IOCs), the incident responder can detect malicious activity triggers and respond quickly to a similar intrusion at an earlier stage. However, in order to implement IOCs in critical infrastructures, we need to understand their contexts and requirements. Unfortunately, there is no survey paper in the literature on IOC in the ICS environment and only limited information is provided in research articles. In this paper, we describe different standards for IOC representation and discuss the associated challenges that restrict security investigators from developing IOCs in the industrial sectors. We also discuss the potential IOCs against cyber-attacks in ICS systems. Furthermore, we conduct a critical analysis of existing works and available tools in this space. We evaluate the effectiveness of identified IOCs’ by mapping these indicators to the most frequently targeted attacks in the ICS environment. Finally we highlight the lessons to be learnt from the literature and the future problems in the domain along with the approaches that might be taken