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Given how smart today’s malware authors have become through employing highly sophisticated techniques, it is only logical that methods be developed to combat the most potent threats, particularly where the malware is stealthy and makes indicators of compromise (IOC) difficult to detect. After the analysis is completed, the output can be employed to detect and then counteract the attack. The goal of this work is to propose a machine learning approach to improve malware detection by combining the strengths of both supervised and unsupervised machine learning techniques. This study is essential as malware has certainly become ubiquitous as cyber-criminals use it to attack systems in cyberspace. Malware analysis is required to reveal hidden IOC, to comprehend the attacker’s goal and the severity of the damage and to find vulnerabilities within the system.

This research proposes a hybrid approach for dynamic and static malware analysis that combines unsupervised and supervised machine learning algorithms and goes on to show how Malware exploiting steganography can be exposed.

The tactics used by malware developers to circumvent detection are becoming more advanced with steganography becoming a popular technique applied in obfuscation to evade mechanisms for detection. Malware analysis continues to call for continuous improvement of existing techniques. State-of-the-art approaches applying machine learning have become increasingly popular with highly promising results.

Cyber security researchers globally are grappling with devising innovative strategies to identify and defend against the threat of extremely sophisticated malware attacks on key infrastructure containing sensitive data. The process of detecting the presence of malware requires expertise in malware analysis. Applying intelligent methods to this process can aid practitioners in identifying malware’s behaviour and features. This is especially expedient where the malware is stealthy, hiding IOC.

This paper aims to illustrate the scope and challenges of using computer-aided content analysis in international marketing with the aim to capture consumer sentiments about COVID-19 from multi-lingual tweets.

The study is based on some 35 million original COVID-19-related tweets. The study methodology illustrates the use of supervised machine learning and artificial neural network techniques to conduct extensive information extraction.

The authors identified more than two million tweets from six countries and categorized them into PESTEL (i.e. Political, Economic, Social, Technological, Environmental and Legal) dimensions. The extracted consumer sentiments and associated emotions show substantial differences across countries. Our analyses highlight opportunities and challenges inherent in using multi-lingual online sentiment analysis in international marketing. Based on these insights, several future research directions are proposed.

First, the authors contribute to methodology development in international marketing by providing a “use-case” for computer-aided text mining in a multi-lingual context. Second, the authors add to the knowledge on differences in COVID-19-related consumer sentiments in different countries. Third, the authors provide avenues for future research on the analysis of unstructured multi-media posts.

This case study paper aims to explore the complexities and challenges of epidemic response and public health surveillance in Native American and Indigenous American communities in the United States and find viable solutions. This paper explores these topics through the emergence and impact of the hantavirus pulmonary syndrome (HPS) within the Navajo Nation in the United States using critical incident analysis and best practices.

This project is a case study paper based on a topical review of the literature. A topical review of the literature is a comprehensive exploration of the current body of knowledge within a particular research field. It is an important tool used by scholars and practitioners to further the development of existing knowledge as well as to identify potential directions for future research (Fourie, 2020). Such a paper can provide a useful insight into the various aspects of the process that the researcher may have overlooked, as well as highlighting potential areas of improvement (Gall et al., 2020). It can also provide a useful source of ideas and inspiration for the researcher as it can provide an overview of the various approaches used by other researchers in the field (Göpferich, 2009). Case study papers using a topical review of the literature have been used to help frame and inform research topics, problems and best practices for some time. They are typically used to explore a topic in greater depth and to provide an overview of the literature to improve the world of practice to provide a foundation for future comprehensive empirical research. Case study papers can provide research value by helping to identify gaps in the literature and by providing a general direction for further research. They can also be used to provide a starting point for research questions and hypotheses and to help identify potential areas of inquiry.

This study explores best practices in public health surveillance and epidemic response that can help strengthen public health infrastructure by informing the development of effective surveillance systems and emergency response plans, as well as improving data collection and analysis capabilities within Native American and Indigenous American communities in the United States that also have the option to include new technologies like artificial intelligence (AI) with similar outbreaks in the future.

The literature review did not include any primary data collection, so the existing available research may have limited the findings. The scope of the study was limited to published literature, which may not have reported all relevant findings. For example, unpublished studies, field studies and industry reports may have provided additional insights not included in the literature review. This research has significant value based on the limited amount of studies on how infectious diseases can severely impact Native American communities in the United States, leading to unnecessary and preventable suffering and death. As a result, research on viable best practices is needed on the best practices in public health surveillance and epidemic response in Native American and Indigenous American communities through historical events and critical incident analysis.

Research on public health surveillance and epidemic response in Native American communities can provide insights into the challenges faced by these communities and help identify potential solutions to improve their capacity to detect, respond to and prevent infectious diseases using innovative approaches and new technologies like AI.

More research on public health surveillance and epidemic response can inform policies and interventions to improve access to healthcare for Native American populations, such as increasing availability of healthcare services, providing culturally appropriate health education and improving communication between providers and patients. By providing better public health surveillance and response capacity, research can help reduce the burden of infectious diseases in Native American communities and ultimately lead to improved public health outcomes.

This paper aims to identify the interaction of different intervention strategies implemented in Malaysia towards flattening the curve of COVID-19 cases. Since the outbreak of COVID-19, many approaches were adopted and implemented by the Malaysian government. Some strategies gained quick wins but with negative unintended consequences after execution, whereas other strategies were slow to take effect. Learning from the previous strategies is pivotal to avoid repeating mistakes.

This paper presents the cause, effect of and connection among the implemented COVID-19 intervention strategies using systems thinking through the development of a causal loop diagram. It enables the visualisation of how each implemented strategy interacted with each other and collectively decreased or increased the spread of COVID-19.

The results of this study suggested that it is not only essential to control the spread of COVID-19, but also to prevent the transmission of the virus. The Malaysian experience has demonstrated that both control and preventive strategies need to be in a state of equilibrium. Focusing only on one spectrum will throw off the balance, leaving COVID-19 infection to escalate rapidly.

The developed feedback loops provided policy makers with the understanding of the merits, pitfalls and dynamics of prior implemented intervention strategies before devising other effective intervention strategies to defuse the spread of COVID-19 and prepare the nation for recovery.

This study is aimed at assessing the information security management practice with a focus on banking card security in selected financial institutions in Ethiopia, using an international information security standard as a benchmark. It is to identify the gaps and recommend best security practices to help financial institutions meet the required security compliance.

Two financial sectors were purposively selected. A total of twenty-five respondents (IT executives and IT staff) were included in the study. Quantitative data was collected using the PCI-DSS (Payment Card Industry Data Security Standard) security standard questionnaire. In addition, observation and document analysis were made.

The result shows that most of the essential security management activities in the financial sectors do not comply with the international security standard. Similarly, the level of most of the indispensable security requirements that should be in place is found to be below the acceptable level. The study also revealed major security factors that prohibit the financial sectors from PCI-DSS security standard compliance.

This study assessed the information security management practice with a focus on banking card security and tried to figure out the limitations of security practices of the organizations surveyed based on the standard adopted. The topic has not been well explored especially in the Ethiopia context. Hence, the result can positively influence security policies, particularly in the banking sector.

The purpose of this study was to explore 232 service providers’ and policymakers’ experiences of supporting children’s well-being during the pandemic, across sectors, in 22 countries – including Kenya, the Philippines, South Africa, India, Scotland, Sweden, Canada and the USA, in the last quarter of 2020.

A smartphone survey delivered via a custom-built app containing mostly open-ended questions was used. Respondents were recruited via professional networks, newsletters and social media. Qualitative content analysis was used.

The findings reveal numerous system-level challenges to supporting children’s well-being, particularly virus containment measures, resource deficiencies and inadequate governance and stakeholder coordination. Those challenges compounded preexisting inequalities and poorly affected the quality, effectiveness and reach of services. As a result, children’s rights to an adequate standard of living; protection from violence; education; play; and right to be heard were impinged upon. Concurrently, the findings illustrate a range of adaptive and innovative practices in humanitarian and subsistence support; child protection; capacity-building; advocacy; digitalisation; and psychosocial and educational support. Respondents identified several priority areas – increasing service capacity and equity; expanding technology use; mobilising cross-sectoral partnerships; involving children in decision-making; and ensuring more effective child protection mechanisms.

This study seeks to inform resilience-enabling policies and practices that foster equity, child and community empowerment and organisational resilience and innovation, particularly in anticipation of future crises.

Using a novel approach to gather in-the-moment insights remotely, this study offers a unique international and multi-sectoral perspective, particularly from low- and middle-income countries.

The highly contagious coronavirus and the rapid spread of COVID-19 disease have generated a global public health crisis, which is being addressed at various local and global scales through social distancing measures and guidelines. This is coupled with debates about the nature of living and working patterns through intensive utilisation of information and telecommunication technologies, leading to the social and institutional acceptability of these patterns as the “new normal”. The primary objective of this article is to instigate a discourse about the potential contribution of architecture and urban design and planning in generating knowledge that responds to pressing questions about future considerations of post pandemic architecture and urbanism. Methodologically, the discussion is based on a trans-disciplinary framework, which is utilised for conceptual analysis and is operationalized by identifying and discoursing design and planning implications. The article underscores relevant factors; originates insights for areas where future research will be critically needed, through key areas: a) Issues related to urban dynamics are delineated from the perspective of urban and human geography, urban design and planning, and transportation engineering; b) Questions that pertain to socio-spatial implications and urban space/ urban life dialectics stem from the field of environmental psychology; and c) Deliberations about new environments that accommodate new living/working styles supervene from ethnographical and anthropological perspectives. The article concludes with an outlook that captures key aspects of the needed synergy between architectural and urban education, research, and practice and public health in a post pandemic virtual and global world.

The purpose of the study is to identify cybersecurity threats that hinder the adoption of digital banking and provide sustainable strategies to combat cybersecurity risks in the banking industry.

Systematic literature review guidelines were used to conduct a quantitative synthesis of empirical evidence regarding the impact of cybersecurity threats and risks on the adoption of digital banking.

A total of 84 studies were initially examined, and after applying the selection and eligibility criteria for this systematic review, 58 studies were included. These selected articles consistently identified identity theft, malware attacks, phishing and vishing as significant cybersecurity threats that hinder the adoption of digital banking.

With the country’s banking sector being new in this area, this study contributes to the scant literature on cyber security, which is mostly in need due to the myriad breaches that the industry has already suffered thus far.

This study aims to, first, propose a valid and reliable scale to document the COVID-19 Pandemic Shopping Experience (CPSE) and, second, determine the impact of its variables on the postpurchase shopping experience (PPSE).

For scale development, published studies were scanned and the variables were shortlisted. These shortlisted variables were validated by 52 faculties from four universities in Saudi Arabia. Data were collected from 318 respondents to purify the CPSE Scale. In Study 2, a path analysis was performed on a sample of 354 respondents to determine the individual impact of each variable on PPSE.

A total of 14 items were found to be aligned under four variables, social distance (SD), shop hygiene, operational time and entertainment venues. SD was found to have the greatest influence on PPSE, followed by operational time and shop hygiene.

This research has important implications for retailers to initiate changes in store layout so that they can implement social distancing by physically marking stickers on the floors and by placing barricading on billing counters. Store hygiene can be ensured by making sanitizers and hand gloves available at the entry points, periodically cleaning the floor and sanitizing the premises. Rationing the operating time proved to be an effective tool to minimize the exposure time, thereby limiting consumers' time inside the store.

To the best of the authors’ knowledge, this is the first study to propose a full-scale measure of the customer shopping experience (SE) during a pandemic. This scale can be generalized to measure SE in similar situations.

This review aims to provide synoptic documentation on acclaimed anecdotal plant-based remedies used by Latin America and the Caribbean (LAC) communities to manage COVID-19. The theoretical approaches that form the basis for using the anecdotally claimed phytotherapies were reviewed against current scientific evidence.

In this paper plant-based remedies for managing COVID-19 were searched on social and print media to identify testimonies of people from different communities in LAC countries. Information was extracted, evaluated and reviewed against current scientific evidence based on a literature search from databases such as Journal Storage (JSTOR), Excerpta Medica Database (EMBASE), SpringerLink, Scopus, ScienceDirect, PubMed, Google Scholar and Medline to explore the scientific basis for anecdotal claims.

A total of 23 medicinal plants belonging to 15 families were identified as phytotherapies used in managing COVID-19 in LAC communities.

The plant-based remedies contained valuable phytochemicals scientifically reported for their anti-inflammatory, antiviral, antioxidant and anticancer effects. Anecdotal information helps researchers investigate disease patterns, management and new drug discoveries. The identified acclaimed plant-based remedies are potential candidates for pharmacological evaluations for possible drug discovery for future pandemics.