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Portugal has been confronted with a succession of crises in recent years. This article explores the differences in the way that, in Portugal, the welfare regime tackled the Great Recession context (financial, euro, sovereign debt, structural adjustment crises) and COVID‐19 crisis through very different policy responses. The fact that the governments in office acted differently when faced with realities that were close in time but very distinct, generates a paired comparative scenario, without forgetting the interim period. Supported by a plural methodological approach that gathers information from various sources, the outcomes reveal important aspects about the policy direction of changes and in terms of socio‐economic indicators. First, policy responses have followed three dynamics in tension: Retrenchment, Mitigation, and Expansion. Second, the policies make a difference, producing distinct outcomes in terms of socioeconomic indicators (unemployment, inequality, poverty). Third, the responses to crises induced more "radical" measures (towards Retrenchment or Expansion), which are not consistent with interim situations. Finally, while the austeritarian response was part of the government in office's program, this was not the case during the pandemic, when the response was involuntary and unprogrammed. This means that, in being a provisional and dated response, there is a high risk that in the near future there will be a resumption of Mitigation or even Retrenchment policies. [ABSTRACT FROM AUTHOR]

The article's primary purpose is to highlight the importance of cybersecurity for Internet of Things (IoT) devices. Due to the widespread use of such devices in everyone's daily and professional lives, taking care of their security is essential. This security can be strengthened by raising awareness about the vulnerabilities and risks of these devices among their manufacturers and users. Therefore, this paper shows the results of several years of work regarding building vulnerabilities and exploiting databases, with a particular focus on IoT devices. We highlight multiple unique features of our solution, such as aggregation, correlation, and enrichment of known vulnerabilities and exploits collected from 12 different sources, presentation of a timeline of threats, and combining vulnerability information with exploits. Our databases have more than 300,000 entries, which are the result of aggregating and correlating more than 1,300,000 entries from 12 different databases simultaneously, enriched with information from unstructured sources. We cover the innovative utilization of Artificial Intelligence (AI) to support data enrichment, examining the usage of the Light Gradient-Boosting Machine (LGBM) model to automatically predict vulnerability severity and Mistral7B to categorize vulnerable products, which, especially in the case of IoT devices, is critical due to the diversity of nomenclature. Social media and various unstructured sources are prominent places for gathering information. Retrieving data from them is much more complex than from structured databases, but the information there is normally supplied at a faster rate. Thus, we added Mastodon monitoring to enhance our threat timelines. [ABSTRACT FROM AUTHOR]

The study explored rural livelihood sustainability in South Asia and Africa through a bibliometric analysis and systematic review approach. The purpose of the study was to identify the trend of scholarly discourse, the dominant themes that have attracted scholarly interest over the past decade, and to shed light on the emerging opportunities for enhancing rural livelihood sustainability. The study carefully selected 139 articles sourced from Scopus, Web of Science, Google Scholar, and other institutional websites. Our findings revealed noticeable growth in scholarly output over the past decade and identified some scholars with noteworthy contributions. Notably, it was found that the impact of climate change, drought, poverty, and food security on rural livelihoods has largely dominated the scholarly investigations over the period. However, the potentials of pyrolis, biochar, and dryland forestry for rural livelihood sustainability were found to be underexplored. In light of these insights, we recommend the scholarly community develop much interest in less explored areas that equally hold great potential for enhancing rural livelihoods. We also recommend that rural livelihood programming by policymakers must seek the integration of indigenous knowledge and be tailored to strengthen the resilience of rural households against the perils of climate change and weather variability. [ABSTRACT FROM AUTHOR]

The impact of the COVID-19 pandemic on custodial institutions has been the subject of intense scrutiny. During the pandemic, many international jurisdictions failed to develop clear and child-focussed plans for the management of children in custody, instead relying on strategies developed for adult populations. Presenting the findings from the United Kingdom's (England Wales) first empirical in-depth exploration of the impacts of COVID-19 on children at each stage of the Youth Justice System, this article discusses the devastating effect on incarcerated children. The pandemic exacerbated existing failures in the children's secure estate, eradicated children's rights and exposed children to increased vulnerabilities. We present an urgent need for a fundamental ideological reconsideration of the purpose of custody for children. [ABSTRACT FROM AUTHOR]

Due to the widespread acceptance of ChatGPT, implementing large language models (LLMs) in real-world applications has become an important research area. Such productisation of technologies allows the public to use AI without technical knowledge. LLMs can revolutionise and automate various healthcare processes, but security is critical. If implemented in critical sectors such as healthcare, adversaries can manipulate the vulnerabilities present in such systems to perform malicious activities such as data exfiltration and manipulation, and the results can be devastating. While LLM implementation in healthcare has been discussed in numerous studies, threats and vulnerabilities identification in LLMs and their safe implementation in healthcare remain largely unexplored. Based on a comprehensive review, this study provides new findings which do not exist in the current literature. This research has proposed a taxonomy to explore LLM applications in healthcare, a threat model considering the vulnerabilities of LLMs which may affect their implementation in healthcare, and a security framework for the implementation of LLMs in healthcare and has identified future avenues of research in LLMs, cybersecurity, and healthcare. [ABSTRACT FROM AUTHOR]

Database systems have consistently been prime targets for cyber-attacks and threats due to the critical nature of the data they store. Despite the increasing reliance on database management systems, this field continues to face numerous cyber-attacks. Database management systems serve as the foundation of any information system or application. Any cyber-attack can result in significant damage to the database system and loss of sensitive data. Consequently, cyber risk classifications and assessments play a crucial role in risk management and establish an essential framework for identifying and responding to cyber threats. Risk assessment aids in understanding the impact of cyber threats and developing appropriate security controls to mitigate risks. The primary objective of this study is to conduct a comprehensive analysis of cyber risks in database management systems, including classifying threats, vulnerabilities, impacts, and countermeasures. This classification helps to identify suitable security controls to mitigate cyber risks for each type of threat. Additionally, this research aims to explore technical countermeasures to protect database systems from cyber threats. This study employs the content analysis method to collect, analyze, and classify data in terms of types of threats, vulnerabilities, and countermeasures. The results indicate that SQL injection attacks and Denial of Service (DoS) attacks were the most prevalent technical threats in database systems, each accounting for 9% of incidents. Vulnerable audit trails, intrusion attempts, and ransomware attacks were classified as the second level of technical threats in database systems, comprising 7% and 5% of incidents, respectively. Furthermore, the findings reveal that insider threats were the most common non-technical threats in database systems, accounting for 5% of incidents. Moreover, the results indicate that weak authentication, unpatched databases, weak audit trails, and multiple usage of an account were the most common technical vulnerabilities in database systems, each accounting for 9% of vulnerabilities. Additionally, software bugs, insecure coding practices, weak security controls, insecure networks, password misuse, weak encryption practices, and weak data masking were classified as the second level of security vulnerabilities in database systems, each accounting for 4% of vulnerabilities. The findings from this work can assist organizations in understanding the types of cyber threats and developing robust strategies against cyber-attacks. [ABSTRACT FROM AUTHOR]

Cerebral palsy (CP) is a neurological disorder that dissipates body posture and impairs motor functions. It may lead to an intellectual disability and affect the quality of life. Early intervention is critical and challenging due to the uncooperative body movements of children, potential infant recovery, a lack of a single vision modality, and no specific contrast or slice-range selection and association. Early and timely CP identification and vulnerable brain MRI scan associations facilitate medications, supportive care, physical therapy, rehabilitation, and surgical interventions to alleviate symptoms and improve motor functions. The literature studies are limited in selecting appropriate contrast and utilizing contrastive coupling in CP investigation. After numerous experiments, we introduce deep learning models, namely SSeq-DL and SMS-DL, correspondingly trained on single-sequence and multiple brain MRIs. The introduced models are tailored with specialized attention mechanisms to learn susceptible brain trends associated with CP along the MRI slices, specialized parallel computing, and fusions at distinct network layer positions to significantly identify CP. The study successfully experimented with the appropriateness of single and coupled MRI scans, highlighting sensitive slices along the depth, model robustness, fusion of contrastive details at distinct levels, and capturing vulnerabilities. The findings of the SSeq-DL and SMSeq-DL models report lesion-vulnerable regions and covered slices trending in age range to assist radiologists in early rehabilitation. [ABSTRACT FROM AUTHOR]

Cultural perspectives on disability shape how disabled women (DW) are perceived and treated in the Yoruba culture, thereby creating an avenue for uniquely gendered exposure to vulnerabilities. The study examined how the socio-cultural construction of disability exposes DW to vulnerabilities in Lagos State. Critical Disability Theory and an exploratory research design were adopted. Primary data were collected through qualitative methods. Twelve in-depth interviews were conducted with vulnerable DW who were selected through snowball sampling. Ten key informant interviews were conducted with purposively selected state actors (the Police, Judiciary, and Lagos State Office of Disability Affairs (LASODA)) and non-state actors (the Disabled People Organization and culture custodians). The data were analyzed using narrative content analysis. Findings revealed that disability is perceived as a limitation of DW, which ensues from the barriers erected by society concerning their impairments. Therefore, disability is largely regarded as a social construct rather than a medical construct. Disabled women construct themselves as 'normal" or "equal' beings in society. However, their significant others socio-culturally constructed them variously as Abirun, Alaare, Elesu, Oosa, asexual, and intellectually deficient in Lagos. These negative constructions were influenced by cultural and belief systems about disability, which expose DW in Lagos to multiple risks and vulnerabilities with harmful consequences for their life chances. [ABSTRACT FROM AUTHOR]

This review explores the relationships between gender and climate change, focusing on Africa, South Asia, and Latin America. It draws attention to the differences in how women, men, and others are impacted by climate change, emphasizing vulnerabilities due to lack of access to resources and decision-making authority. We highlight the role gender-sensitive environmental institutions have in moderating how gender relations are affected by climate change. We assess gender sensitivity in environmental institutions, climate adaptation, and mitigation initiatives through regional comparisons, considering the different roles, responsibilities, and demands of women, men, and other intersectional groups within policies and initiatives to identify opportunities and difficulties in enacting gender-sensitive policies. The analysis shows widespread recognition of the significance of tackling gender-related concerns in the context of climate change and concludes that while progress is evident, there is room for improvement in addressing biases, stereotypes, and specific challenges, especially concerning climate change. [ABSTRACT FROM AUTHOR]

This study aims to enhance the cybersecurity framework of pacemaker devices by identifying vulnerabilities and recommending effective strategies. The objectives are to pinpoint cybersecurity weaknesses, utilize machine learning to predict security breaches, and propose countermeasures based on analytical trends. The literature review highlights the transformation of pacemaker technology from basic, fixed-rate devices to sophisticated systems with wireless capabilities, which, while improving patient care, also introduce significant cybersecurity risks. These risks include unauthorized entry, data breaches, and lifethreatening device malfunctions. The methodology in this study utilizes a quantitative research approach using the WUSTL-EHMS-2020 dataset, which includes network traffic features, patients' biometric features, and attack label. The step-by-step method of machine learning prediction includes data collection, data preprocessing, feature engineering, and models' training using Support Vector Machines (SVM) and Gradient Boosting Machines (GBM). The implementation results used evaluation metrics like accuracy, precision, recall, and F1 score to show that GBM model outperformed the SVM model. The GBM model achieved higher accuracy of 95.1% compared to 92.5% for SVM, greater precision of 99.6% compared to 96.7% for SVM, better recall of 94.9% compared to 42.7% for SVM, and a higher F1 score of 76.3% compared to 59.0% for SVM, making GBM model more effective in predicting cybersecurity threats. This study concludes that GBM is an effective machine learning model for enhancing pacemaker cybersecurity by analyzing network traffic and biometric data patterns. Future recommendations for improving the pacemaker cybersecurity include implementing GBM model for threat predictions, integration with existing security measures, and regular model updates and retraining. [ABSTRACT FROM AUTHOR]

Background/Objectives: Emergency Medical Response Systems (EMRSs) play a vital role in delivering medical aid during natural and man-made disasters. This quantitative research delves into the analysis of risk and effectiveness within Serbia's Emergency Medical Services (EMS), with a special emphasis on how work organization, resource distribution, and preparedness for mass casualty events contribute to overall disaster preparedness. Methods: The study was conducted using a questionnaire consisting of 7 sections and a total of 88 variables, distributed to and collected from 172 healthcare institutions (Public Health Centers and Hospitals). Statistical methods, including Pearson's correlation, multivariate regression analysis, and chi-square tests, were rigorously applied to analyze and interpret the data. Results: The results from the multivariate regression analysis revealed that the organization of working hours (β = 0.035) and shift work (β = 0.042) were significant predictors of EMS organization, explaining 1.9% of the variance (R2 = 0.019). Furthermore, shift work (β = −0.045) and working hours (β = −0.037) accounted for 2.0% of the variance in the number of EMS points performed (R2 = 0.020). Also, the availability of ambulance vehicles (β = 0.075) and financial resources (β = 0.033) explained 4.1% of the variance in mass casualty preparedness (R2 = 0.041). When it comes to service area coverage, the regression results suggest that none of the predictors were statistically significant. Based on Pearson's correlation results, there is a statistically significant correlation between the EMS organization and several key variables such as the number of EMS doctors (p = 0.000), emergency medicine specialists (p = 0.000), etc. Moreover, the Chi-square test results reveal statistically significant correlations between EMS organization and how EMS activities are conducted (p = 0.001), the number of activity locations (p = 0.005), and the structure of working hours (p = 0.001). Conclusions: Additionally, the results underscore the necessity for increased financial support, standardized protocols, and enhanced intersectoral collaboration to strengthen Serbia's EMRS and improve overall disaster response effectiveness. Based on these findings, a clear roadmap is provided for policymakers, healthcare administrators, and EMS personnel to prioritize strategic interventions and build a robust emergency medical response system. [ABSTRACT FROM AUTHOR]

Abstract The study explored rural livelihood sustainability in South Asia and Africa through a bibliometric analysis and systematic review approach. The purpose of the study was to identify the trend of scholarly discourse, the dominant themes that have attracted scholarly interest over the past decade, and to shed light on the emerging opportunities for enhancing rural livelihood sustainability. The study carefully selected 139 articles sourced from Scopus, Web of Science, Google Scholar, and other institutional websites. Our findings revealed noticeable growth in scholarly output over the past decade and identified some scholars with noteworthy contributions. Notably, it was found that the impact of climate change, drought, poverty, and food security on rural livelihoods has largely dominated the scholarly investigations over the period. However, the potentials of pyrolis, biochar, and dryland forestry for rural livelihood sustainability were found to be underexplored. In light of these insights, we recommend the scholarly community develop much interest in less explored areas that equally hold great potential for enhancing rural livelihoods. We also recommend that rural livelihood programming by policymakers must seek the integration of indigenous knowledge and be tailored to strengthen the resilience of rural households against the perils of climate change and weather variability.

Background: Given the pervasive connectivity and integration of the Internet of Things (IoT) devices into daily life, system security is of utmost significance in the modern era. The article examines escalating concerns regarding the security of the Internet of Things, its inherent vulnerabilities, and the necessary precautions required to safeguard our interconnected global environment. Objective: With forecasts indicating that the IoT ecosystem will comprise over 50 billion interconnected devices by 2030, the alarming 300% increase in IoT intrusions over the past year underscores the urgency of addressing this issue. Methodology: In this article, IoT security challenges are divided into three primary categories which include device vulnerabilities, network vulnerabilities, and data security vulnerabilities. Results: Our findings emphasize the necessity for end users, developers, and manufacturers to follow security best practices and take part in security training. The study discovered that successful DDoS attacks use infected IoT devices 65% of the time and there is still legacy firmware on 70% of those devices making them susceptible. Possible solutions that are currently under investigation include secure elements, machine learning anomaly detection intrusion detection systems, and blockchain-based device authentication. Most prominently, proactive IoT security solutions have reduced 85% of the security vulnerabilities for organizations; it is truly a remarkable achievement. Conclusion: Understanding the security dynamic of the IoT ecosystem is a very demandable job as it keeps on changing, and so does the knowledge about it. To ensure that the IoT remains powerful and transformative in a connected society, this article will take a look further into the increasing risks, vulnerabilities, scary stats as well as effective solutions. It underscores the need for strong measures to protect security and greater awareness.

As AI is deployed increasingly in defensive systems, hostile assaults have increased. AI-driven defensive systems are vulnerable to attacks that exploit flaws. This article examines the approaches used to resist AI-based cybersecurity systems and their effects on security. This paper examines existing literature and case studies to demonstrate how attackers modify AI models. These include avoidance, poisoning, and data-driven assaults. It also considers data breaches, system failures, and unauthorized access if a hostile effort succeeds. The report recommends adversarial training, model testing, and input sanitization to address these issues. It also stresses the need for monitoring and updating AI algorithms to adapt to changing opponent tactics. This paper emphasizes the need to limit hostile strike threats using real-life examples and statistics. To defend AI-driven cybersecurity systems from complex threats, cybersecurity specialists, AI researchers, and policymakers must collaborate across domains. This article provides full guidance for cybersecurity and AI professionals. It describes the complex issues adversarial assaults create and proposes a flexible and robust architecture to safeguard AI-driven cybersecurity systems from emerging threats. [ABSTRACT FROM AUTHOR]

This study is dedicated to identifying and understanding regional vulnerabilities within countries, focusing particularly on those susceptible to frequent and devastating disasters, such as Japan. The primary objective of this research is to delve into the dynamics of disaster preparedness, aiming to propose a robust framework that local governments can collaboratively establish with their citizens, demonstrating active leadership throughout the process. The central focus of this research is Mihama Town in Fukui Prefecture. This locale was chosen to evaluate the awareness levels of disaster preparedness among its residents, providing a microcosmic view of broader regional challenges. Simultaneously, the study seeks to scrutinize the leadership components integral to formulating public-sector disaster response policies. The research analyzed survey responses from 333 participants to distill crucial requirements for ensuring the safety and security of the town’s population. Utilizing structural equation modeling, the results of this study underscore the nuanced nature of building trust in municipal disaster preparedness. The research advocates a dual-pronged strategy. First, it emphasizes enhancing citizen services as a tangible manifestation of consistent government support for day-to-day community activities. Second, it highlights the necessity of maintaining clear and decisive leadership to ensure the sustained long-term viability of the community. The study stresses that alongside continually improving citizen services, an unwavering commitment to the local government’s message of “sustainable city development” is pivotal. The study’s proposed framework serves as a guide for local governments to not only prepare for but also effectively respond to disasters. It outlines the importance of a cohesive strategy that incorporates citizen engagement, robust leadership, and consistent service enhancement as pillars of disaster preparedness.

Climate change will affect New Zealand’s diverse range of climatic systems in different ways. The impacts on agriculture are expected to vary with geographical location and the specific biophysical requirements of different crops and agricultural systems. To improve our understanding of these impacts, key biophysical vulnerabilities for the main farming systems in New Zealand were identified and modelled using the daily projected climate scenario data. Results show high spatial variability but a general pattern of suitability ranges for crops moving south, and animal health issues intensifying and also moving south. Sediment loads are projected to increase, particularly in soft-rock hill country areas in the North Island. The modelling approach offers opportunities for analysing the temporal significance of projected changes, such as the timing and duration of drought, the effect on timing of phenological stages, the timing of pasture growth and the effect on animal farm systems. [ABSTRACT FROM AUTHOR]

Labour migration, other than being a key driver of economic growth and development, is also associated with inconsistent human rights practices. This paper furthers the understanding of links between migration and human trafficking in Andhra Pradesh, India. It applies IOM's Determinants of Vulnerability Framework to assess and analyse the various ways in which vulnerabilities of the migrant unorganised and casual labourers are constructed as they are forced to migrate for livelihood security. The study employed a mixed-methods approach which included a survey of 5888 individuals, seven case studies, five focus group discussions and 121 key informant interviews. The paper confirms that migration, by itself, does not lead to trafficking. A number of intersecting, inter-related factors at individual, household, community, and structural levels add to risks or provide protection against trafficking to a migrant before, during or after the process of migration. Relatedly, the paper argues that the process of migration is a continuum between vulnerability, unsafe migration, and trafficking. [ABSTRACT FROM AUTHOR]

Various data platforms force the individual into constant presence and visibility. However, the ways in which datafied environments relate to experienced vulnerabilities in our everyday lives remain unclear. Through diaries produced by and interviews with participants from three groups who occupy presumably vulnerable positions and who currently live in Finland, we explore the ways in which people challenge expectations and prior assumptions related to forced visibility. Using the concept of tactics developed by de Certeau, we aim to understand how individuals make everyday surveillance culture livable through what we call tactics of invisibility. Based on our analysis, we identify three kinds of tactics in this context: keeping worlds apart, cropping oneself out of the frame, and sidestepping. We interpret tactics of invisibility as ways of shaping a space for oneself illustrate fractures in what previous research has framed as digital resignation. [ABSTRACT FROM AUTHOR]

The global pandemic impacted Asian migrant workers disproportionately. During the first COVID-19 nationwide lockdown, Nepali migrant workers faced many challenges due to widespread misconceptions of them being vectors of COVID-19. This research examines COVID-19 impacts on international and internal Nepali migrant workers. A national survey on the social, economic, and psychological challenges of returning Nepali migrant workers was administered online from 10 May to 20 July 2020. A total of 672 responses were received. Using a binary logistic regression model, the research finds that the domestic migrant workers were less likely to get economic support, expect to borrow money during COVID-19, experience negative changes in their personal lives, and expect the COVID-19 contraction. In contrast, international migrant workers were less likely to return to their pre-pandemic employment. The research exposed long-standing vulnerabilities of migrant workers and identified immediate actions from Nepalese Central, Provincial, and Local governments to address their needs. [ABSTRACT FROM AUTHOR]

As software vulnerabilities can cause cybersecurity threats and have severe consequences, it is necessary to develop effective techniques to discover such vulnerabilities. Fuzzing is one of the most widely employed approaches that has been adapted for software testing. The mutation-based fuzzing approach is currently the most popular. The state-of-the-art American Fuzzy Lop (AFL) selects mutations randomly and lacks knowledge of mutation operations that are more helpful in a particular stage. This study performs a systematic review to identify and analyze existing approaches that optimize the selection of mutation operations. The main contributions of this work are to draw attention to the importance of mutation operator selection, identify optimization algorithms for mutation operator selection, and investigate their impact on fuzzing testing in terms of code coverage and finding new vulnerabilities. The investigation shows the effectiveness and advantages of optimizing the selection of mutation operations to achieve higher code coverage and find more vulnerabilities. [ABSTRACT FROM AUTHOR]

According to theoretical and empirical knowledge, cybersecurity awareness is a crucial issue in cyber security. The main actors in cyber security are people, and one way to reduce risk in cyberspace is to increase knowledge of security concerns. Companies lose money as a result of data breaches and production losses brought on by cyberattacks. Consequently, there has been a surge in research endeavours aimed at comprehending the cybersecurity behaviours of users. The benefit of knowing user behaviours is that researchers and security professionals may utilize this information to start altering behaviours for the sake of cybersecurity. Similar cybersecurity behaviours have been categorized by several research, while the naming systems used vary. Sanctions, a decline in customer loyalty, and damage to one's brand may all arise from data breaches. Business continuity is also impacted by cyberattacks, which make it difficult for organizations to maintain constant production. This paper aims to demonstrate that, in addition to computer science research, behavioural sciences that study user behaviours can offer useful strategies to improve cyber security and lessen the impact of attackers' social engineering and cognitive hacking tactics (i.e., disseminating misleading information). Thus, in this study, we provide fresh insights on the psychological characteristics and individual variances of computer system users that account for their susceptibility to cyberattacks and crimes. Our investigation shows that different computer system users have different cognitive capabilities, which affects their ability to defend against information security threats. In order to improve network and information security, we identify research gaps and suggest possible psychological techniques to help computer system users follow security requirements. [ABSTRACT FROM AUTHOR]

This paper addresses the role of philosophical practice in the development of Aristotelian phronesis to enable younger generation to cope with human vulnerabilities. We study two sessions of philosophical practice involving eleven- and twelve-years old pupils of an educational priority area middle school in Grenoble, France. These activities are inspired by the Lipman's approach of Community of Philosophical Inquiry and the Tozzi's one of democratic and philosophical discussion. Extending our previous research, we investigate more specifically phenomena we refer to as "bimodal metaphorical philosophemes". We define them as sequences of recurring verbal and gestural metaphors that facilitate the co-construction of definitions during philosophical discussions. We show that bimodal metaphorical philosophemes foster the development of phronesis in pre-teens involved in the philosophical discussions we study. In this way, philosophical practices may help future generations cope with human vulnerabilities in the sense described by Cynthia Fleury. [ABSTRACT FROM AUTHOR]

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This paper investigates possible threats and risks to information security arising from the use of VPN products. A combined methodology for assessing the security of VPN products is proposed, which includes the IMECA (Intrusion Modes and Effects Criticality Analysis) method, as well as some so-called static and dynamic methods. This allows you to make an informed choice of a VPN product for secure Internet use, taking into account your personal preferences. The combined vulnerability analysis methodology involves determining the criticality of threats, taking into account the likelihood of their occurrence and implementation, as well as the severity of the consequences. Based on the results of the analysis, the choice of appropriate countermeasures in the form of VPN product features to minimize risks and increase the security of their users is substantiated. The practical significance of the results for improving cybersecurity is determined. The article is based on a study of the features of VPN products and proposes a new approach that includes IMEСA and experimental methods. [ABSTRACT FROM AUTHOR]

Rising levels of risk as cyber‐attackers look to exploit system vulnerabilities threatens the Air Traffic Control industry. Attacks on Air Navigation Service Providers' communications systems may lead to airspace closure and even cause safety issues. This paper presents a novel Model‐Based Systems Engineering method that enables systems engineers, in collaboration with system security and software engineers, to perform threat‐modeling analysis of cyber‐physical systems early in the system development process and incorporate mitigation strategies into the system design. The proposed model‐based method covers few security concepts, including misuse cases, system assets, threats, risks, vulnerabilities, and security control identification. The study found that the proposed method is suitable for conducting security analysis for complex cyber‐physical systems early in the system development process. [ABSTRACT FROM AUTHOR]

A closed season policy has emerged as an ocean governance strategy aimed at protecting and conserving fish stocks across countries and coastal areas. Its implementation has produced traces of vulnerabilities, and forms of livelihood adaptations and alternative livelihood opportunities. However, little is known about how these occur among gender groups. This paper therefore focuses on the gender dimensions of vulnerabilities, adaptations and alternative livelihoods during the closed season in Elmina, Ghana, within the feminist political ecology framework. It employed Focus Group Discussions (FGDs) from purposively selected fishermen and fish processors. The study found significant differences in the vulnerability patterns among the gender groups, albeit some similarities. We further observed more fluid roles among the women than the men because the women were ready to undertake alternative livelihood options that were traditionally male-based during the closed season. Based on these results, we contend that political decisions toward environmental sustainability may create vulnerability and fluid adaptation patterns which may vary among gender groups in the light of their differential patterns of access, control and positionalities within the fishing industry. [ABSTRACT FROM AUTHOR]