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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.

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.

The emergence of the COVID-19 pandemic in late 2019 led to a global crisis of unprecedented scale and complexity that disrupted almost every aspect of human life. The pandemic has taken people, institutions and governments by surprise, so the impact of the virus has been profound and far-reaching. The rapid and relentless spread of the pandemic has challenged global health systems, strained economies, altered daily routines in educational settings and at work, and tested the resilience of communities worldwide. Different studies have identified vulnerabilities in the world's ability to respond to health emergencies at the individual and societal levels. This study presents a systematic literature review and theoretical analysis of the disruptions caused by COVID-19 to help formulate strategies that encourage flexibility and resilience in the face of such complex and interconnected disruptions. The article analyzes the consequences of the COVID-19 pandemic through the prism of two main theories: the theory of situational crisis communications (type of crisis, its history, responsibility, perceived seriousness, predictable probability, crisis communications strategies, post-crisis reputation), as well as the theory of social learning (learning through observation, modeling and imitation, positive and negative reinforcement in the formation of behavior). In addition, the nature of society's adaptation to the challenges of the COVID-19 pandemic is also considered through the prism of the theory of subversive innovations (progress in communication technologies, new methods of remote work and education, the entry of social networks into the business world, the introduction of asynchronous communication). The article summarizes the scientific progress on the following main consequences of the COVID-19 pandemic in the workplace, healthcare system, and education. The study provides recommendations on the steps that individuals, institutions and governments can take to increase readiness and ability to adapt to the next crisis (interdisciplinary cooperation, analysis of communication strategies, system analysis). The analysis conducted in the article also made it possible to outline the most promising directions for further qualitative intervention studies (in-depth case studies taking into account the specific context of regions, organizations or communities to identify effective and ineffective policies and practices; qualitative interviews with key stakeholders to understand the intricacies of decision-making in the context of the pandemic crisis); qualitative action studies (building community resilience, collaborative research efforts involving policymakers, health experts and community representatives to develop crisis response policies jointly) and quantitative studies (analysis of pandemic spread, impact of vaccination on disease control, analysis of the economic effects of the pandemic, etc.).

Abstract The traditional electrical grid has to be digitally improved as digitalization and effective integration of renewable energy bring better efficiency, intelligence, and safety into the grid; hence, the transition from the traditional grid to a smart grid. A smart grid is a modernized and digitalized standard electrical infrastructure that has a key component known as the advanced metering infrastructure (AMI). AMI, also known as smart metering, is a key technological enabler of the smart grid that allows automatic collection and reporting of power-consumed data via two-way communication networks. However, the collected power consumption data is confidential; hence, its privacy must be maintained. Similarly, for the benefit of the smart grid to be consistently maximized, the AMI data and network security must always be intact despite the evolving threats and attacks targeted at it. This paper provides a comprehensive review of the existing vulnerabilities/attacks, security and privacy challenges associated with the smart metering data and network system, its open issues, and future direction. The major contributions of this review paper lie in the AMI vulnerabilities, AMI state-of-the-art security schemes with their pros and cons, its communication protocols analysis, and its emerging security measures. This gave enumerated recommendations for the efficiency improvement of AMI security in terms of its latency reduction while implementing efficient security measures in its future work.

The bulk electrical system, a critical infrastructure for societal functionality, must meet the electricity demands of end-users sustainably, economically, and in compliance with standards. The concept of power system resiliency has gained significant attention as vulnerabilities and potential attacks could lead to substantial losses. This paper distinguishes power system resiliency from reliability through a detailed literature review. It discusses the development of quantitative metrics from operational and infrastructural perspectives to better understand this emerging concept. We categorize the threats into natural disasters and cyber threats, evaluating their impacts on power system components. The integration of smart grid technologies—including demand response, electric vehicles, distributed generation, energy storage systems, and microgrids—is explored to demonstrate how they enhance resilience against external shocks. This review not only offers a comprehensive analysis of load restoration techniques through smart grid practices but also identifies future challenges, such as adapting to increasingly severe climate conditions, advancing cybersecurity measures to match evolving threats, and ensuring the scalability of resilient systems to meet growing energy demands. These challenges highlight the necessity for innovative research and strategic planning to strengthen power systems against a broad spectrum of emerging threats. This work serves as a critical reference for researchers and planners dedicated to enhancing resiliency strategies.

Slovenia has been repatriating persons of Slovenian descent and their immediate family members from poverty-stricken Venezuela since 2019. The article explores the innate, situational, and structural vulnerabilities of the repatriates, focusing in particular on the vulnerabilities affecting their well-being and leading to emotional distress. The vulnerabilities are examined through the lens of time, i.e., before, during, and after the acquisition of the status of a repatriate, and in the context of specific age-related integration challenges. The article shows that their preferred emotional support is provided by the close-knit community of Venezuelan repatriates with whom they share the same language, culture, and experience of repatriation and integration and by the Catholic church through mass, confession, and church gatherings.

Resumo Diante da recente concentração produtiva na pecuária leiteira do Rio Grande do Sul, o artigo teve como objetivo analisar os principais fatores que afetam a perspectiva de permanência dos produtores na atividade. O estudo se embasou no conceito teórico de intitulamentos e sobre uma perspectiva sistêmica de análise da vulnerabilidade. Foram entrevistados 110 produtores de diferentes regiões do estado e de quatro estratos de volume de produção de leite. A análise da perspectiva futura de permanência ou saída da atividade partiu da construção de dois modelos de regressão logística, baseados na percepção dos produtores sobre 44 indicadores de vulnerabilidade. Do total de entrevistados, 29% disseram que pretendem deixar a pecuária leiteira no curto ou médio prazo. Os resultados das duas regressões logísticas confeccionadas apontam para o fato de que os indicadores internos e externos de vulnerabilidade exercem influência sobre a tomada de decisão. Quanto aos indicadores internos, destaca-se que a disponibilidade de mão de obra, de sucessores e de terra impactam diretamente na perspectiva de continuidade. Tratando-se dos indicadores do contexto externo, nota-se que a expansão da produção de grãos tem pressionado os preços das terras e, por consequência disso, influenciado nas possibilidades de abandono da produção leiteira.

Vulnerable places are usually the targets of terrorist attacks everywhere in the world. The scenario is quite the same in Nigeria. Boko Haram and other terrorist groups in Nigeria have attacked ordinary citizens and infrastructure like schools and hospitals. Especially crowded places are the main targets of the terrorists. To mitigate this security challenge, the Nigerian government factored in the protection of soft targets in its National Counter-Terrorism Strategy (NACTEST). The second pillar of NACTEST, known as “to secure,” is in charge of this assignment. The NACTEST document was launched in 2014 by President Jonathan as a standing policy to combat terrorism in Nigeria. It is expected that this strategy needs to be evaluated since it has been in operation for more than half a decade. The focus of this paper is to examine the extent to which the Nigerian government has successively protected soft targets from terrorism attacks. The paper makes use of both primary and secondary data as sources of data gathering and content analysis for data analysis. The research makes use of the NACTEST document and bases its evaluation on the specified objectives of the NACTEST second pillar, “to secure." It also adopts asymmetric theory as its theoretical framework. The paper discovered that the Nigerian government has, to a large extent, successively protected the vulnerable, like civilian citizens, utilities, and infrastructure. However, sporadic attacks by terrorists are equally a challenge that the government needs to handle seriously. The paper recommended, among others, that the government should provide needed resources, both human and material, for security and better performance.

This study presents a literature review of the vulnerabilities faced by the agricultural sector (economic vulnerabilities, climate vulnerabilities, and social vulnerabilities) and a bibliometric analysis of the studies published on this topic. The agricultural sector is highly sensitive to current economic, climate, and social changes. The results show that research on this topic has grown rapidly in recent times, demonstrating the increased interest from academia. It was also noted that the topic is being addressed by researchers in 69 countries. The US has participated most in the formation of the literature on the topic of vulnerabilities in the agricultural sector, followed by Brazil and China. The most common research topics studied include issues related to education, health, and food security, but also social issues (politics, population, inequality, etc.).

Refactoring is one of the techniques mostly employed by software developers to improve the quality attributes of their systems. However, little has been done to investigate how refactoring operations specifically aimed at improving the internal structure of software can impact its security. Refactoring usually entails different code change operations including the decomposition of classes, methods, and the reallocation of code elements. While this refinement aims to improve the internal design of a system, it might inadvertently disperse security-critical code elements throughout the codebase. Consequently, such dispersion could affect the software attack surface. To this end, this paper presents an empirical study conducted on 30 open-source software systems that were developed in Python, C, and Javascript. The study scrutinized two subsequent versions of each subject application to uncover the refactoring operations applied and the trend of the software attack surface. Specifically, the study focused on the injection or removal of bugs, code smells and other vulnerabilities aiming to discern the impact of refactorings on the software attack surface. Data was collected using well-known tools, namely SonarQube, RefDiff, and PyReff. The findings suggest that refactorings can have multiple impacts (i.e., positive, negative, or neutral) on bugs, code smells, and vulnerabilities. The findings further confirm that developers must be aware of the combination or sequence of refactoring operations that can improve software quality without compromising its security.

Cybersecurity is vitally important to all critical network and information systems (Critical N&IS). Effective information security comprises multiple layers of defense working together to protect Critical N&IS. When developing a proper cybersecurity, the only considered are especially technical layers, but effective penetration attacks often involve a mix of both the social and technical vectors of attack. The fact that the human error is one of the vital layers that could be a potential weakness for any system that incorporates humans needs a special attention and should be handled at the EU level. Given the increasing number of incidents created by insufficiently trained operators, a strategic necessity arises: the mandatory training and certification of Critical N&IS’ operators across the EU. This objective could be fulfilled through a new Regulation (The Cyber Competences Act) for laying down measures to complement achieving a high common level of cybersecurity within the European Union.

Indonesia merupakan negara rawan bencana apabila dilihat dari aspek geografis, klimatologis, maupun demografisnya. Letak geografis Indonesia yang berada di antara 2 benua dan 2 samudera menyebabkan potensi bencana meningkat terutama secara geologis. Letak Indonesia pada 3 lempeng, yaitu Lempeng Eurasia, Lempeng Indo-Australia, dan Lempeng Pasifik berkontribusi pada kerawanan bencana tersebut. Kabupaten Blitar dengan proporsi wilayah dataran tinggi yang besar membuat wilayah tersebut menjadi rawan terhadap potensi bencana longsor. Penelitian ini akan membahas mengenai kajian tingkat risiko bencana tanah longsor di wilayah Kabupaten Blitar melalui analisis kerentanan bencana, kapasitas bencana, dan bahaya yang dipadukan melalui teknik overlay menjadi tingkat risiko bencana tanah longsor. Hasil penelitian menunjukkan bahwa Kabupaten Blitar didominasi oleh area dengan tingkat kerawanan bencana tinggi hingga sangat tinggi. Penelitian ini diharapkan membantu upaya mitigasi pengurangan dampak bencana tanah longsor di Kabupaten Blitar.

Dynamic analysis is a technique that is used to fully understand the internals of a system at runtime. On Android, dynamic security analysis involves real-time assessment and active adaptation of an app’s behaviour, and is used for various tasks, including network monitoring, system-call tracing, and taint analysis. The research on dynamic analysis has made significant progress in the past years. However, to the best of our knowledge, there is a lack in secondary studies that analyse the novel ideas and common limitations of current security research. The main aim of this work is to understand dynamic security analysis research on Android to present the current state of knowledge, highlight research gaps, and provide insights into the existing body of work in a structured and systematic manner. We conduct a systematic literature review (SLR) on dynamic security analysis for Android. The systematic review establishes a taxonomy, defines a classification scheme, and explores the impact of advanced Android app testing tools on security solutions in software engineering and security research. The study’s key findings centre on tool usage, research objectives, constraints, and trends. Instrumentation and network monitoring tools play a crucial role, with research goals focused on app security, privacy, malware detection, and software testing automation. Identified limitations include code coverage constraints, security-related analysis obstacles, app selection adequacy, and non-deterministic behaviour. Our study results deepen the understanding of dynamic analysis in Android security research by an in-depth review of 43 publications. The study highlights recurring limitations with automated testing tools and concerns about detecting or obstructing dynamic analysis.

Smart Grids (SGs) rely on advanced technologies, generating significant data traffic across the network, which plays a crucial role in various tasks such as electricity consumption billing, actuator activation, resource optimization, and network monitoring. This paper presents a new approach that integrates Machine Learning (ML), Blockchain Technology (BT), and Markov Decision Process (MDP) to improve the security of SG networks while ensuring accurate storage of events reported by various network devices through BT. The enhanced version of the Proof of Work (PoW) consensus mechanism ensures data integrity by preventing tampering and establishing the reliability of known and unknown attack detection. The proposed versions of PoW, namely GPoW 1.0 and GPoW 2.0, aim to make the consensus process more environmentally friendly.

Open-source Programmable Logic Controller (OpenPLC) software is designed to be vendor-natural and run on almost any computer or low-cost embedded devices e.g., Raspberry Pi, Ardunio, and other controllers. The aim of this project is to introduce an affordable and practical alternative solution for the high-cost of real hardware PLCs, and has successfully gained substantial interest within both the research and industrial communities. Due to its popularity grows, understanding its security vulnerabilities and implementing effective mitigation strategies become crucial. Through a combination of threat modeling, vulnerability analysis, and practical experiments, this article provides valuable insights for developers, researchers, and engineers aiming to deploy OpenPLC securely in industrial environments. To this end, we first conducted an in-depth analysis aimed to shed light on various security challenges and vulnerabilities within the OpenPLC project. These encompass issues such as unauthorized access, vulnerabilities in communication protocols, concerns regarding data integrity, the absence of robust encryption mechanisms, etc. After that, we showed the research community what the consequences of those vulnerabilities would be if they are exploited. To this end, we performed a sophisticated control logic injection attack that maliciously modifies the user program run on the OpenPLC Runtime. Our injection was stealthy and not detected by the legitimate user. Finally, we introduced a security-enhanced OpenPLC software called OpenPLC Aqua. Our developed software is equipped with a set of security solutions designed specifically to address the vulnerabilities to which current OpenPLC versions are prone. All our attack codes as well OpenPLC Aqua software are publically available.

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.

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.

The COVID-19 pandemic has had wide-ranging implications on the academic community and there have been numerous commentaries on the effects of the pandemic on qualitative health research. However, the vulnerabilities faced by participants and researchers during the pandemic have remained underexplored. Addressing this gap, this reflective article discusses the intersecting challenges and opportunities arising for participants and researchers in qualitative health research during the pandemic through the lens of layered vulnerability. Vulnerability, as a layered concept, provides novel insight to discussions on the effects of the pandemic as it provides a depth of insight into the multifaceted and dynamic nature of vulnerabilities, while considering individual differences and contexts. Reflecting on the research we conducted during the pandemic, we draw out the layers of vulnerability that both participants and researchers faced during the research process, as well as the obligations and strategies we developed to mitigate these vulnerabilities. We discuss the intersectionality of individual characteristics and the digitisation of work and life, including the impact of moving qualitative health research online and the use of creative methodological approaches. Our article highlights how, through engaging with their own vulnerabilities throughout the research process, researchers can develop creative and new solutions for qualitative research which mitigate the increased vulnerabilities participants faced during the pandemic.

The current context for the development of smart cities is affected by the economic and social uncertainties generated by the multiple crises that are manifesting themselves in the European space both through the declining geopolitical conflict and the economic recession that the European Union is going through. We aim to conduct a study on smart city vulnerabilities in the current context of uncertainty in order to identify the contribution of smart governance components to increase social welfare. We will also develop a regression model of social welfare for smart cities using empirical and econometric methods (multiple linear regression). The results of the study will highlight the level of smart city development of 10 European regions (Bulgaria, Denmark, France, Germany, Hungary, the Netherlands, Poland, Romania, Sweden and the EU27 average) over the period 2012-2021. The results will be useful for national decision-makers to improve public policies related to smart city development in Europe.

The subject of this study is to ensure the cybersecurity of systems of multifunctional UAV fleets (SMF UAV). The purpose of this study is to identify and analyze the risks associated with the cybersecurity of multi-functional UAV fleets, develop models of threats, vulnerabilities, and attacks, and conduct IMECA analysis of cyber-attacks. Tasks: 1) analyze threats that may affect the security of multifunctional UAV fleets; 2) identify system vulnerabilities and their possible consequences in case of exploitation; 3) develop models of the system infrastructure and threats, vulnerabilities, and attacks, considering the specifics of the functionality and communication between system elements; 4) perform a risk-based analysis, identifying and classifying potential threats and their impact. The following results were obtained. The following results were obtained. 1. Cybersecurity threats to multifunctional UAV fleets are described and classified. 2. Identified and analyzed system vulnerabilities and their potential consequences. 3. Developed models of threats, vulnerabilities, and cyberattacks, considering the specifics of the UAV fleet. 4. Conducted a risk-based analysis, determined the level of threat, and developed recommendations for improving the cybersecurity of the UAV fleet based on the results of the IMECA analysis. Conclusions. The research emphasizes the importance of the developed model and tool for the detection and analysis of cyber threats to the SMF UAV. This allows increasing the cybersecurity and reliability of the system and ensuring timely response to cyber threats. Areas for further research: development of a model and method to consider the specifics of cyber threats and the technological characteristics of the SMF infrastructure; development and implementation of proactive protection tools in the context of combined cyber-attacks; and expansion of the scope of these tools in various industries, including smart cities.

Large Brazilian cities, such as Rio de Janeiro, suffer serious environmental problems caused by informal settlements (IS), such as advances in the degradation of surface waters involving anthropic pressures resulting from uncontrolled urban growth, lack of sanitation or disasters related to climate events, creating a gap in relevant information about environmental health in urban IS. Therefore, it is essential to assess the health conditions of IS and the local population's perception of their living conditions. This study aimed to evaluate, by online form and public data, the sanitary conditions of the third largest IS in Brazil, the Rio das Pedras community, which was located on the banks of the Jacarepaguá Lagoon complex. The analysis revealed that 35% of respondents reported releasing domestic sewage directly into the river near their homes. Furthermore, 83% of the participants reported that they disposed of urban solid waste inappropriately. About 21% of residents reported falling ill due to direct contact with unsafe water after flood events. Public managers, concerned with advancing sustainability agendas and mitigating the risks to environmental health related to the lack of adequate sanitation services, should invest in actions that reflect the perception of the local population, proposing more appropriate socio-environmental solutions. HIGHLIGHTS Analysis of the sanitary conditions of the main slum profile in Brazil.; Perception of environmental reality reported essentially by residents.; Pointing out the various forms of improper disposal of domestic effluents in water bodies.; Part of the population is in constant health vulnerability due to contact with unsafe water.; Most interviewees are aware of contributing to environmental degradation.;

The terminology of radicalization started to be acknowledged after the 9/11 events, a turning point for international security that marked the beginning of the War on Terror. Practitioners, policymakers, and researchers in the field of countering terrorism focused more and more on the concept of radicalization as a precursor of terrorism, in the sense of being the starting point for preventing the terrorism phenomenon. In this regard, the past terrorist attacks in Europe awakened awareness about the necessity of identifying the incipient signs of radicalization as an early warning instrument for avoiding the probability of manifesting a terrorist attack. Even though the Global Terrorism Index has evaluated Romania as one of the countries with the lowest risks of terrorism at the international level for the past decade, it is still important to improve the mechanisms for preventing radicalization. In this consideration, Romania could be indirectly impacted by factors related to the global or regional dynamics of terrorism. This paper aims to develop a pattern of radicalization vulnerabilities and observed trends in Romania. In this idea, the analysis of the past terrorist attempts in Romania emphasizes important details in terms of trends of radicalization. Furthermore, the analysis of the specific radicalization features in Romania is focused on identifying the vulnerabilities, following the case study conclusions on radicalized Romanian citizens and radicalized foreigners that were expelled by the national courts.

Vehicle automation has been in the works for a long time now. Automatic brakes, cruise control, GPS satellite navigation, etc. are all common features seen in today's automobiles. Automation and artificial intelligence breakthroughs are likely to lead to an increase in the usage of automation technologies in cars. Because of this, mankind will be more reliant on computer-controlled equipment and car systems in our daily lives. All major corporations have begun investing in the development of self-driving cars because of the rapid advancement of advanced driver support technologies. However, the level of safety and trustworthiness is still questionable. Imagine what the assailants could do if they had access to a car. Control of braking, acceleration and even steering by an attacker can have disastrous results. Most of the assaults against autonomous vehicle software and hardware are covered in this study, along with their prospective consequences. This work explores an extended analysis of the security threat and cyber-attacks on different sensors and perception systems in autonomous vehicles. This work also showed machine learning-based possible defensive techniques to prevent the security threat. An overview of most of the conceivable assaults against autonomous vehicle software and hardware and their prospective consequences is presented in this study.

Abstract Inequities shape the everyday experiences and life chances of individuals at the margins of societies and are often associated with lower health and particular challenges in accessing quality treatment and support. This fact is even more dramatic for those individuals who live at the nexus of different marginalized groups and thus may face multiple discrimination, stigma, and oppression. To address these multiple social and structural disadvantages, intersectional approaches have recently gained a foothold, especially in the public health field. This study makes an empirically informed argument for the merits of increasing the use of intersectional frameworks in the mental health field. In the mental health field, the potential for greater attention to multiple unjustified disadvantages appears to be of particular importance, as many mental health service users already face stigma and discrimination because of their mental health issues and thus may benefit particularly frequently and far-reachingly from effective problem awareness about multiple disadvantages. Intersectional approaches may help address the complexity, interdependence, and mutual constitution of social inequalities better than previous approaches that examined only one category of sociostructural stratification. By helping to identify the needs of those at the greatest risk of poor health, intersectional frameworks and tools can contribute not only to better address the needs of multiple disadvantaged individuals with mental health issues but also to the promotion of equity in the field of mental health, contributing to the reduction of health disparities.

This research investigates the intricacies of X.509 certificates within a comprehensive corporate infrastructure. Spanning over two decades, the examined enterprise has heavily depended on its internal certificate authority and Public Key Infrastructure (PKI) to uphold its data and systems security. With the broad application of these certificates, from personal identification on smart cards to device and workstation authentication via Trusted Platform Modules (TPM), our study seeks to address a pertinent question on how prevalent are weak RSA keys within such a vast internal certificate repository. Previous research focused primarily on key sets publicly accessible from TLS and SSH servers or PGP key repositories. On the contrary, our investigation provides insights into the private domain of an enterprise, introducing new dimensions to this problem. Among our considerations are the trustworthiness of hardware and software solutions in generating keys and the consequential implications of identified vulnerabilities on organizational risk management. The obtained results can contribute to enhancing security strategies in enterprises.

IP cameras and digital video recorders, as part of the Internet of Surveillance Things (IoST) technology, can sometimes allow unauthenticated access to the video feed or management dashboard. These vulnerabilities may result from weak APIs, misconfigurations, or hidden firmware backdoors. What is particularly concerning is that these vulnerabilities can stay unnoticed for extended periods, spanning weeks, months, or even years, until a malicious attacker decides to exploit them. The response actions in case of identifying the vulnerability, such as updating software and firmware for millions of IoST devices, might be challenging and time-consuming. Implementing an air-gapped video surveillance network, which is isolated from the internet and external access, can reduce the cybersecurity threats associated with internet-connected IoST devices. However, such networks can also be susceptible to other threats and attacks, which need to be explored and analyzed. In this work, we perform a systematic literature review on the current state of research and use cases related to compromising and protecting cameras in logical and physical air-gapped networks. We provide a network diagram for each mode of exploitation, discuss the vulnerabilities that could result in a successful attack, demonstrate the potential impacts on organizations in the event of IoST compromise, and outline the security measures and mechanisms that can be deployed to mitigate these security risks.

Societal security has become nowadays an important pair of lenses for discussing identity in a multilayered fashion within the context of an enlarged security concept. The complexity deriving from that engenders the necessity to identify and use new tools for reliably defining communities and their specific identities in order to better understand how state-wise strategies and policies can raise security risks when disregarding those communities’ needs and interests. In this respect, the goal of this article is to demonstrate the benefits of employing a gender-based perspective in defining societal security. Hence, it focuses on the possible correlations that can be conceptually identified between societal security and gender perspective. Then, the article exemplifies how a gender-based analysis can contribute to better societal security approaches by discussing Romania’s strategic approach to the Covid-19 pandemic and the possible observations deriving from that.

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.

Тhis article compares and contrasts macro- and micro-foundational explanations about disinformation and resilience in Europe as a result of Russia’s war in Ukraine. It presents micro-level data about the shifting public opinion in Europe after Russia’s invasion in Ukraine on Feb 24, 2022 on the topics of NATO and EU support and favorability, sympathy for Ukraine and condemnation of Russia, including support for sanctions against Moscow (Pew Research Center 2021, 2022). The study compares and contrasts traditional macro-level analytical frameworks such as deterrence, institutionalization and adaptation. I argue that a combination of macro- (or institutional) and micro-level factors (associated with the idiosyncrasies of the domestic public opinion) best explain the shifting attitudes since the beginning of the War in Ukraine. Against the backdrop of NATO and the EU’s increased resilience, a new group or sub-club of “vulnerable” allies has emerged among some central and east European nations. The article evaluates different constraints and vulnerabilities and makes recommendations how to reduce misinformation and contestation in these states.

Bug bounty schemes make use of outside ethical hackers to find and fix a variety of security flaws, guaranteeing quicker and more affordable problem solving. Better confidence in and image of the company in the cybersecurity space, faster solving issues, and increased community collaboration are some of its results. Computer vision relies on face detection, which has several uses. This article uses convolutional neural networks (CNNs) and an error reward algorithm in the facial recognition simulation library to enhance face detection. Trainers trained CNNs to detect faces from other visual components and extract human facial traits, making them powerful facial identification tools. These networks classify and extract face characteristics automatically, obtaining approaching 100% identification rates. CNNs have greater identification rates and easier face-image extraction than earlier methods. Network architecture determines its performance, transcending machine learning methodologies. This article suggests a bug reward scheme to discover and resolve bugs in the face recognition library. The program has helped Google find flaws in its intelligent systems, including model manipulation and adversarial assaults. These activities enhance AI safety and security studies, highlight possible concerns, and promote AI safety. CNN-based facial recognition models enhance accuracy and offer advantages over previous approaches. The CNN-based method and Bug Bounty software improved the facial recognition library.

Bangladesh has been severely affected by the extreme heatwave that is affecting most of Asia. Extreme climate events, particularly heatwave impacts on the food system, pose risks to human health in Bangladesh, explicitly in the north-west part of the country. The association between the heatwave, food security and health are narrowly described in the existing literature, resulting in a research lacuna related diverse component of food system that are particularly vulnerable to the heatwave. The current study therefore aims to develop a framework for understanding the nexus between heatwave, food security, and human health, which will ultimately help to improve livelihood resilience in Bangladesh. A comprehensive literature review was conducted to examine the link between heat waves, food security including human health (HFH) to explore the vulnerabilities in the food system in Rajshahi, Bangladesh. Additionally, the current study conducted a case study on the tribal community (e.g., Santals) of Rajshahi to understand heatwave, food security and health nexus. There is evidence that critical activities in the food system are prone to risk to heat waves. It is complex how heatwaves propagate along the food system and impact elucidative dimensions of food security to impact human health impacts. Different types of disruption related to heatwave can indirectly affect human health by compromising food security, a critical factor of health. The case study of the current investigation reveals that human health can also be affected by the physical impact of the heat wave on the food system, particularly with regard to diet-related impacts and food-borne diseases within the tribal community. In the study, we propose to offer a novel analytical framework to examine and respond to the relationship between heat waves, food security and human health. The investigation provide a benchmark to policymakers, academia, and relevant stakeholders to examine and understand current and future heatwave risks and to develop adaptation strategies to build livelihood resilience in Bangladesh explicitly for tribal community.

A hostile intelligence entity is trying to identify or create behavioural vulnerabilities – professional dissatisfaction, unrealistic expectations, gambling, spending/borrowing beyond means, expensive lifestyle, financial difficulties, so as to exploit them to influence the person to reveal confidential information or to adopt certain decisions. One of the ways of counterintelligence protection of data and decision is the awareness by individuals of vulnerabilities and reality that can be exploited by a hostile entity. And the purpose of a test on vulnerabilities is to evaluate the level of awareness and, implicitly, self -protection

Abstract With the advent of the Internet, the activities of individuals and businesses have expanded into the online realm. As a result, vulnerabilities that result in actual breaches can lead to data loss and program failure. The number of breaches is increasing every year, as is the number of vulnerabilities. To address this problem, current research focuses on the detection of vulnerabilities using static analysis techniques. To prevent the propagation of vulnerabilities, a new paradigm is needed to quickly detect vulnerabilities, analyze them, and take actions such as blocking or removing them. Recently, artificial intelligence algorithms such as deep learning have been introduced for vulnerability detection. In this paper, we propose a vulnerability detection model, V-CNN, which aims to detect CWE/CVE (Common Weakness Enumeration/Common Vulnerabilities and Exposures) using CNN (convolutional neural network). We trained CWE for deep learning and redefined vulnerabilities based on CWE. We propose an experimental algorithm to improve vulnerability detection. The accuracy of the proposed V-CNN model is 98%, which exceeds the 95% of the random forest model. Therefore, our V-CNN has excellent correctness detection performance in the field of vulnerability detection. The V-CNN vulnerability detection algorithm can be used instead of static analysis to detect various security vulnerabilities.

In recent years, the use of deep learning models for deploying sentiment analysis systems has become a widespread topic due to their processing capacity and superior results on large volumes of information. However, after several years’ research, previous works have demonstrated that deep learning models are vulnerable to strategically modified inputs called adversarial examples. Adversarial examples are generated by performing perturbations on data input that are imperceptible to humans but that can fool deep learning models’ understanding of the inputs and lead to false predictions being generated. In this work, we collect, select, summarize, discuss, and comprehensively analyze research works to generate textual adversarial examples. There are already a number of reviews in the existing literature concerning attacks on deep learning models for text applications; in contrast to previous works, however, we review works mainly oriented to sentiment analysis tasks. Further, we cover the related information concerning generation of adversarial examples to make this work self-contained. Finally, we draw on the reviewed literature to discuss adversarial example design in the context of sentiment analysis tasks.

The Internet of Things (IoT) and blockchain are emerging technologies that have attracted attention in many industries, including healthcare, automotive, and supply chain. IoT networks and devices are typically low-powered and susceptible to cyber intrusions. However, blockchains hold considerable potential for securing low-power IoT networks. Blockchain networks provide security features such as encryption, decentralisation, time stamps, and ledger functions. The integration of blockchain and IoT technologies may address many of the security concerns. However, integrating blockchain with IoT raises several issues, including the security vulnerabilities and anomalies of blockchain-based IoT networks. In this paper, we report on our experiments using our blockchain test bed to demonstrate that blockchains on IoT platforms are vulnerable to DDoS attacks, which can also potentially lead to device hardware failures. We show that a number of anomalies are visible during either a DDoS attack or IoT device failure. In particular, the temperature of IoT hardware devices can exceed 90 °C during a DDoS attack, which could lead to hardware failure and potential fire hazards. We also found that the Block Transaction Rate (BTR) and network block loss percentage can increase due to corrupted hardware, with the BTR dropping to nearly zero blocks/sec and a block loss percentage of over 50 percent for all evaluated blockchains, and as high as 81.3 percent in one case. Our experiments demonstrate that anomalous temperature, latency, bandwidth, BTR, and network block loss percentage can potentially be used to identify DDoS attacks.

Vulnerabilities are often accompanied by cyberattacks. CVE is the largest repository of open vulnerabilities, which keeps expanding. ATT&CK models known multi-step attacks both tactically and technically and remains up to date. It is valuable to correlate the vulnerability in CVE with the corresponding tactic and technique of ATT&CK which exploit the vulnerability, for active defense. Mappings manually is not only time-consuming but also difficult to keep up-to-date. Existing language-based automated mapping methods do not utilize the information associated with attack behaviors outside of CVE and ATT&CK and are therefore ineffective. In this paper, we propose a novel framework named VTT-LLM for mapping Vulnerabilities to Tactics and Techniques based on Large Language Models, which consists of a generation model and a mapping model. In order to generate fine-tuning instructions for LLM, we create a template to extract knowledge of CWE (a standardized list of common weaknesses) and CAPEC (a standardized list of common attack patterns). We train the generation model of VTT-LLM by fine-tuning the LLM according to the above instructions. The generation model correlates vulnerability and attack through their descriptions. The mapping model transforms the descriptions of ATT&CK tactics and techniques into vectors through text embedding and further associates them with attacks through semantic matching. By leveraging the knowledge of CWE and CAPEC, VTT-LLM can eventually automate the process of linking vulnerabilities in CVE to the attack techniques and tactics of ATT&CK. Experiments on the latest public dataset, ChatGPT-VDMEval, show the effectiveness of VTT-LLM with an accuracy of 85.18%, which is 13.69% and 54.42% higher than the existing CVET and ChatGPT-based methods, respectively. In addition, compared to fine-tuning without outside knowledge, the accuracy of VTT-LLM with chain fine-tuning is 9.24% higher on average across different LLMs.

Abstract: Female genital mutilation is one harmful traditional practice that is highly prevalent in African countries such as Guinea, Sierra Leone, the Gambia, Mauritania, Mali, and Burkina Faso, as well as in Sudan, Egypt, and Ethiopia. In these harmful traditional practices, women have an essential role as both perpetrators and victims of FGM. In developing countries, the issues of FGM receive little attention in restoring and maintaining the well-being and health of women, and the governments have not given them due attention. The socio-cultural settings also make women’s lives miserable. This study tried to assess the community perception, socio-cultural reasons, and the consequences of FGM on women’s livelihoods. It also integrates the issue of FGM in the study areas with the UN SDGs goals for 2030. In this study, a qualitative approach supported by a phenomenological study design has been employed. Twelve affected (or females) were included in the research, as were six circumcisers/female genital cutters or experts, five victim household parents, two focus group discussions, and the life histories of the three victims of female genital mutilation in the region. The findings of this study reveal that women are victims of harmful traditional practices in general and FGM in particular. Women’s cultural influence on tradition makes them accept that religion orders so. Women support FGM as they are less educated than men and because of the secondary social status they have in society. To minimize the problem, both governmental and non-governmental organizations should work collaboratively with community members.

Background: The global 2030 Agenda covers a range of interconnected issues which need interdisciplinary and holistic approaches to improve human well-being and protect the natural environment. The COVID-19 pandemic has brought to light critical inequities in society and policy gaps in health services. As highlighted through analyses of the interlinkages among the Sustainable Development Goals (SDGs), connections between human health and well-being and the environment, can help support new policy needs in addressing systemic health crises, including widespread pandemics. Method: We identify links between the COVID-19 crisis and multiple SDGs in the context of Brazil based on a review of the current literature in the health sector.Findings: We identify synergistic connections between 88 out of 169 SDG targets and COVID-19, notably around themes such as City Environment, Contextual Policies and the value created by improved Information and Technology. Using the context of the Brazilian National Health Service (SUS) highlights recurrent interconnections from the focal point of target 3.8. This includes topics such as challenges for universal healthcare coverage, budget allocation, and universalisation. Conclusions: The framework developed for supporting policy-making decisions and the design of toolkits for dealing with future health-related emergency scenarios offers a practical solution in the health sector. It is worth noting that progress and action on public health systems and policies must go hand in hand with addressing existing socio-economic vulnerabilities in society. This is vital for tackling future pandemics and simultaneously addressing the SDGs.

The current study seeks to explore the vulnerabilities typically encountered by female migrants in the informal sector in Dhaka city. It used a qualitative research approach, purposively selecting four areas from Dhaka city. Twenty-five semi-structured in-depth interviews during eight months of participant observation were conducted to accomplish the study objective. The authors used the capability approach theory to elucidate the phenomenon of vulnerability experienced by female migrants in the informal sector. The thematic data analyses were performed using the Granheim approach and NVivo 12 software. The findings of this study suggest that migrant women who work on the street face a number of significant challenges. These challenges include sexual assault and harassment, social stigma and cultural barriers, financial obstacles, and extortion and bribery. The authors recommend that governments provide access to state credits, social security, health insurance, and other forms of social protection for informal sector workers. The finding revealed that informal workers are often excluded from these essential benefits, making it difficult for such workers to expand their businesses or have a safety net in case of illness, unemployment, or other shocks.

Several studies have examined the humanitarian Civil-Military Cooperation (CIMIC) in post-conflict environments. However, there has been limited focus on establishing and making available an institutional setup for child welfare, which harnesses CIMIC experiences in the post-conflict rehabilitation phase. This paper aims to address this gap in the Newly Merged Districts (NMDs) of Pakistan, where the local population experienced a series of crises in the form of terrorism, subsequent military operations, and conflict-induced internal displacement, making children, in particular, extremely vulnerable. In doing so, the paper outlines the underreported vulnerabilities related to the children of NMDs and further identifies the related institutional dynamics of CIMIC in the immediate post-conflict environment. The key findings encompass the delineation of direct and indirect vulnerabilities and the identification of a lack of distinction between child welfare and protection for adequate redressal policies. Regarding the pre-existing institutional infrastructure, the study confirms the prominent role of national and international development organizations and further validates the discord between relevant government departments in providing child welfare services. Furthermore, this research argues that the Pakistan military deployed throughout the former Federally Administered Tribal Areas (FATA) effectively utilized the pre-existing social-tribal hierarchy to provide protection and development services. The research suggests that the Provincial Disaster Management Authority (PDMA), specifically through its Gender and Child Cell, collaborates closely with the Social Welfare Department, which is responsible for providing child protection and welfare services in the post-merger environment. The objective of this collaborative effort is to facilitate the effective and practical implementation of Child Protection Units (CPUs) in the NMDs.

Programmable logic controllers (PLCs) are indispensable in critical infrastructures and industrial control systems. The increasing demand for enhanced cost-effectiveness and production efficiency has driven automation manufacturers to integrate PLC-based applications and systems with external networks, such as Internet. Unfortunately, this connectivity has exposed systems to potential malicious attacks from motivated adversaries. Addressing this pressing issue necessitates a comprehensive summary of ongoing research related to PLCs and their related systems. This summary should classify these systems based on disclosed vulnerabilities, potential threats, and proposed security solutions, catering to both scientists and industrial engineers. While several recent surveys have reviewed and discussed PLC security and related topics, they often fell short of covering all essential aspects comprehensively. Furthermore, prior surveys tended to focus on analyzing vulnerabilities at the system level, overlooking the vulnerabilities specific to PLCs themselves. Consequently, their findings failed to effectively secure current operational systems or propose improved solutions for future PLC designs. In this article, we bridge this research gap by providing a detailed review of all aspects concerning the security of PLCs and related systems. This includes vulnerabilities, potential attacks, and security solutions including digital forensics. We aim to offer a precise analysis, addressing the shortcomings of previous studies. Finally, we conclude this article by presenting our recommendations tailored for PLC manufacturers, researchers, and engineers. We hope that these recommendations will contribute to the development of more secure PLCs in the future.

Rapid computer and internet technology advancements have catalyzed continuous breakthroughs and innovations in related fields, significantly impacting social production and individual lifestyles. A critical challenge addressed here is the inadequacy of existing methods for assessing computer vulnerabilities. The vulnerability scoring model for intelligent vehicles (VSMIV) is proposed to solve the issue in intelligent computers. A key aspect involves optimizing the attack vector and attack complexity of common vulnerabilities and exposures (CVEs) to align with the specific behaviour of intelligent computers. The model's effectiveness is enhanced by integrating four distinct indicators: property security, privacy security, functional security, and life security. The diversity ratings indicate that the VSMIV scoring system has the highest diversity of system distribution at 95%, followed by CVSSIoT at 88%, and CVSS with a slightly lower diversity score of 85%. The proposed methodology holds promise in establishing a new paradigm for strengthening the security of computer systems, thereby stimulating their flexibility in the face of emerging threats.

Automatic Dependent Surveillance-Broadcast (ADS-B) is a multiparameter surveillance system designed to improve key segments of air traffic: enabling real-time surveillance, raising safety and efficiency levels, and improving flight information and weather services. ADS-B consists of two subsystems, ADS-B Out and ADS-B In. Although only a complete system, ADS-B In/Out provides numerous benefits (additional situational awareness, more efficient oceanic routing, etc.) FAA and EASA only require ADS-B Out (by January and June 2020, respectively), whereby ADS-B In remains optional. Because of its many advantages, ADS-B In/Out will be popular, but there are some weaknesses, which are primarily related to its cyber vulnerabilities due to insufficient authentication and encryption in the applied protocol. In this paper, an overview of the ADS-B system is presented as an aid to understanding the security problems and the different ways of potential attack. In addition, this review deals with the current state of ADS-B deployment and its future perspective and challenges.

The pervasiveness of complex technological infrastructures and services coupled with the continuously evolving threat landscape poses new sophisticated security risks. These risks are mostly associated with many diverse vulnerabilities related to software or hardware security flaws, misconfigurations and operational weaknesses. In this scenario, a timely assessment and mitigation of the security risks affecting technological environments are of paramount importance. To cope with these compelling issues, we propose an AI-assisted methodological framework aimed at evaluating whether the target environment is vulnerable or safe. The framework is based on the combined application of graph-based and machine learning techniques. More precisely, the components of the target together with their vulnerabilities are represented by graphs whose analysis identifies the attack paths associated with potential security threats. Machine learning techniques classify these paths and provide the security assessment of the target. The experimental evaluation of the proposed framework was performed on 220 artificially generated Active Directory environments, half of which injected with vulnerabilities. The results of the classification process were generally good. For example, the F1-score obtained by the Random Forest classifier for the assessment of vulnerable networks was equal to 0.91. These results suggest that our approach could be applied for automating the security assessment procedures of complex networked environments.

Many share the concern that the Covid-19 pandemic has had devastating impacts on the vulnerable who are already disproportionately at risk of social exclusion. The health-related risks that the pandemic entailed and the challenges that resulted from the associated measures have led to new vulnerabilities for specific groups such as persons with disabilities, persons from a (forced) migrant background, and women/girls. This article will discuss the complexity of the multiple vulnerabilities during the Covid-19 pandemic by relying on data collected from immigrant women with disabilities. To this end, data from two women with disabilities who are members of the historically marginalized Turkish immigrant group in Austria were analyzed with regard to their experiences during the pandemic. Their accounts are analyzed from an intersectional perspective in order to document the effects of peri-post-pandemic measures on the lives of people with multiple disadvantages. The interviews and audio diaries by two immigrant women with disabilities recorded over seven months are used to delve into latent oppression structures and overlapping mechanisms of difficulties embedded in their experiences. The findings show how the multiple identities and struggles of the two women were affected during the pandemic by building upon each other.

The COVID-19 pandemic, the health protection measures, and the policies meant to limit the economic effects of the disease have affected the world's economies on multiple levels, the international trade being one of the most seriously influenced domains. The paper aims to highlight the effects of the pandemic on Romania's current account, as well as some directions of action aimed at improving the external deficit of our country. The methodology used in the article joins the empirical analysis of statistical data and their interpretation, with the identification of causalities. The analysis shows that the uncertainty regarding the evolution of COVID-19 and the measures adopted by the authorities to stop the spread of the coronavirus affected negatively, especially in 2020, the current account, and its way of financing. The paper highlights some elements that can hamper the decrease of the external deficit in the future (the large needs of external financing in the coming years, the dependence of the economy on imports, the unfavourable structure of Romanian exports and imports), as well as some directions of action intended to support the improvement of the external deficit of our country, including supporting the recovery of the economy, reducing the budget deficit, improving the domestic offer, and the research and innovation activity, etc.

The goal of the study – development of specific methodical reasoned proposals on improvement of the mechanism for ensuring sustainable development of the national banking system and its security against external challenges and threats to cyberspace. The scientific novelty consists in a comprehensive analysis of the processes of ensuring the cyber stability of the Russian banking system in the context of escalation of external challenges and threats to the digital economy. The authors used the following methods: general scientific (observation, comparison, measurement, analysis and synthesis, logical reasoning method), specific scientific (static analysis, peer review, graphical method). In the article conducted a critical review of domestic and foreign scientific literature and practical recommendations to ensure the protection of the banking institution from cyber threats in the digital economy; presented a comparative analysis of the organization of the cybersecurity system in the Russian and foreign banking systems; done multidimensional statistical analysis of cyber threats for Russian banks; substantiated recommendations and proposals on organizational, economic and legal improvement of the system of protection of Russian banks from internal and external cyber threats. As a result, it is shown that the main problem points (zones) of the banking system, creating the prerequisites for the occurrence of cyber-risks are: 1) there is no exchange of information on cyber-attacks and their mechanisms; 2) banks interact inefficiently with the state regulator of Internet – Roskomnadzor; 3) low level of competence of bank employees who are responsible for cybersecurity; 4) limited budget of small and medium-sized banks that wouldn’t allow them to care independent cyber-protection units; 5) growing popularity of new fintech services and new fintech companies. The author draws a conclusion that the following measures are necessary for organizational, economic and legal improvement of the system of protection of Russian banks from internal and external cyber threats: the processes of development of banking ecosystems should be intensified; a federal interbank register of cyber fraudsters must be created; a single banking «polygon» for testing cyber threats needs to be developed.

The COVID-19 pandemic has highlighted multiple vulnerabilities and issues around local and regional food systems, presenting valuable opportunities to reflect on these issues and lessons on how to increase local/regional resilience. Using the Fraser Valley Regional District (FVRD) in Canada as a case study, this research employs integrated planning perspectives, incorporating comprehensive-systems, regional, place-based, and temporal considerations, to (1) reflect upon the challenges and vulnerabilities that COVID-19 has revealed about local and regional food systems, and (2) examine what these reflections and insights illustrate with respect to the needs for and gaps in local/regional resilience against future exogenous shocks. The study used a community-based participatory approach to engage local and regional government, stakeholders, and community members living and working in the FVRD. Methods consisted of a series of online workshops, where participants identified impacts related to the food production, processing, distribution, access, and/or governance response components of the local and regional food systems and whether these impacts were short-term (under 3 months), medium-term (3 to 12 months), or long-term (over 1 year) in nature. Findings from the study revealed that food systems and their vulnerabilities are complex, including changes in food access and preparation behaviours, lack of flexibility in institutional policies for making use of local food supply, cascading effects due to stresses on social and public sector services, and inequities with respect to both food security impacts and strategies/services for addressing these impacts. Outcomes from this research demonstrate how including comprehensive-systems, regional, place-based, and temporal considerations in studies on food systems vulnerabilities can generate useful insights for local and regional resiliency planning.