Current Vulnerability Research Articles

New York State Climate Impacts Assessment Chapter 06: Energy.

Energy plays an integral role in New Yorkers' lives. It powers the economy, moves people and goods, keeps homes and workplaces at a livable temperature, and runs critical infrastructure that keeps people healthy and safe. Reliable energy systems are easy to take for granted, but many aspects of these systems are vulnerable to weather and climate hazards. This chapter discusses how climate change is affecting and will increasingly affect New York State's energy supply, delivery, and end uses. It provides insights into current and future climate vulnerabilities as New York's energy system transitions to clean energy sources. This assessment also highlights opportunities to adapt current and future energy systems and to build resilience to climate impacts.

The long-run effect of historical redlining practices on social vulnerability in U.S. cities

Historical redlining practices in the United States date back to the 1930s and have continued to impact cities socially, environmentally, and economically since then. This study explores current social vulnerability inequity among former HOLC (Home Owners' Loan Corporation) neighborhoods with four color-coded grades in 196 U.S. digitized cities. Social vulnerability measurements for each historical HOLC neighborhood were calculated using 2018 census tract-level social vulnerability data through areal apportionment. Kruskal-Wallis tests were employed to compare four grades of former HOLC neighborhoods regarding overall social vulnerability index (SVI), four thematic SVIs (Social economic status, Household composition and disability, Minority status and language, and Housing type and transportation), and SVIs for fifteen social vulnerability factors. After applying multiple comparison corrections, the results indicate significant differences among four HOLC grades concerning overall social vulnerability, four themes, and most of social vulnerability factors. In general, grade A (green) neighborhoods exhibit the lowest vulnerability, while grade D (red) neighborhoods have the highest vulnerability. A similar pattern of social vulnerability inequity persists even after adjusting for inter-city differences in baseline social factors using the city-normalized SVI (CSVI). This finding suggests that urban planners and policymakers should work to reduce social vulnerability inequity across neighborhoods of different grades.

Long-term study of the combined effects of ocean acidification and warming on the mottled brittle star, Ophionereis fasciata.

The global ocean is rapidly changing, posing a substantial threat to the viability of marine populations due to the co-occurrence of multiple drivers, such as ocean warming (OW) and ocean acidification (OA). To persist, marine species must undergo some combination of acclimation and adaptation in response to these changes. Understanding such responses is essential to measure and project the magnitude and direction of current and future vulnerabilities in marine ecosystems. Echinoderms have been recognised as a model in studies of OW-OA effects on marine biota. However, despite their global diversity, vulnerability and ecological importance in most marine habitats, brittle stars (ophiuroids) are poorly studied. A long-term mesocosm experiment was conducted on adult mottled brittle star (Ophionereis fasciata) as a case study to investigate the physiological response and trade-offs of marine organisms to ocean acidification, ocean warming and the combined effect of these two drivers. Long-term exposure of O. fasciata to high temperature and low pH affected survival, respiration and regeneration rates, growth rate, calcification/dissolution and righting response. Higher temperatures increased stress and respiration, and decreased regeneration and growth rates as well as survival. Conversely, changes in pH had more subtle or no effect, affecting only respiration and calcification. Our results indicate that exposure to a combination of high temperature and low pH produces complex responses for respiration, righting response and calcification. We address the knowledge gap of the impact of a changing ocean on ophiuroids in the context of echinoderm studies, proposing this class as an ideal alternative echinoderm for future research.

Enhancing supply chain security and transparency with ai and blockchain integration for future-proof solutions

The objective of this review paper is to examine the integration of Artificial Intelligence (AI) and blockchain technology to enhance supply chain security and transparency, providing future-proof solutions for global industries. As the digital landscape evolves, traditional supply chain management methods face increasing vulnerabilities and inefficiencies. This paper reviews existing literature to assess the current challenges and potential benefits of integrating AI and blockchain in supply chains. The review highlights how AI enhances predictive analytics, demand forecasting, and operational efficiency, while blockchain ensures immutable, decentralized ledgers for real-time tracking and verification of goods. The synergy between these technologies offers unprecedented levels of transparency, enabling stakeholders to detect and respond to anomalies swiftly. Case studies across various industries demonstrate significant improvements in reducing fraud, counterfeiting, and human errors, alongside enhanced compliance with regulatory standards. Conclusions drawn from this review underscore the transformative potential of AI and blockchain in creating resilient, transparent, and secure supply chains. The integration of these technologies not only addresses current vulnerabilities but also lays the foundation for adaptive, intelligent supply chain networks capable of withstanding future disruptions. This paper provides actionable insights and practical frameworks for businesses and policymakers aiming to implement AI and blockchain solutions, emphasizing the importance of strategic planning, cross-industry collaboration, and continuous innovation in achieving long-term supply chain sustainability and security.

UniBin: Assembly semantic-enhanced binary vulnerability detection without disassembly

The widespread reuse of open-source code amplifies the impact of vulnerabilities. Current vulnerability detection methods predominantly rely on binary code similarity comparisons, which involve disassembling to obtain assembly code or control flow graphs. These methods depend on specific disassembly tools and complex preprocessing, limiting their applicability and detection speed. This paper proposes UniBin, a vulnerability detection method based on the multi-layer Transformer encoder. By employing bidirectional LM, unidirectional LM, and sequence-to-sequence LM tasks on both binary and assembly code during the pre-training phase, UniBin learns richer semantic information from binary machine code, enabling efficient similarity comparison without disassembly and mitigating the limitations of disassembly. We cross-compile 55 widely used open-source C projects as datasets. After 52 hours of pre-training and 8 hours of fine-tuning, UniBin reaches an average accuracy of 98.3% in similarity detection across compilation conditions, outperforming the state-of-the-art method. For search tasks across optimization options with a pool size of 1000, the Recall@1 metric improves by 28.2% (from 67.9% to 87.1%). UniBin eliminates dependency on specific disassembly tools and improves end-to-end binary analysis speed by over 36%. In real-world vulnerability detection tasks, UniBin detects all vulnerability functions with the lowest false positive rate of 0.16%.

Intelligent Connected Vehicle Information Security Risks and Countermeasures

The development of intelligent connected vehicles has promoted the upgrading of the transportation system, but it also brings challenges in information security. This paper analyzes the current information security vulnerabilities of intelligent connected vehicles, including attack methods, security vulnerabilities, and protective measures. Firstly, through the analysis of the existing attack methods and their principles, the potential security vulnerabilities and threats are summarized. Then, based on security and cryptography technology, relevant measures for information security protection are proposed to achieve all-round protection of intelligent connected vehicle information. Finally, The paper puts forward the measures to solve the information security problem of intelligent connected vehicle from three aspects: Encryption and Authentication, Firewall and Intrusion Detection System, and Over-the-air (OTA).

Towards designing a comprehensive composite index for social vulnerability to natural hazards in the big data era: potential challenges and partial solutions

AbstractThis study provides a practical definition and framework to measure social vulnerability to natural hazards, addressing gaps in the literature after three decades of Susan Cutter's Place-Based Model. The current social vulnerability index, designed based on available data such as census data, is limited in capturing all aspects of social vulnerability and spatial inequalities. This research explored and proposed a new theoretical perspective and methodological framework for designing a comprehensive index for social vulnerability to natural disasters using emerging big data, which is practical and feasible and can be applied to social vulnerability studies in general and social vulnerability to natural hazards in particular. This research first defines constructs of social vulnerability to natural hazards, including (1) socioeconomic status or conditions, (2) physical infrastructure or accessibility to facilities and services, (3) ecological-environmental conditions, (4) access to security facilities and crime rate, (5) technological inequalities, (6) health conditions of the citizens, and (7) susceptibility. Then, it proposes potential solutions for developing a comprehensive composite index under ideal conditions without (big) data limitations, using the US and the UK as case examples. These solutions are not just theoretical but also practical and feasible, instilling confidence in their implementation. This research offers valuable insights for researchers and policymakers in diverse sectors, supporting the design of effective disaster risk reduction strategies and intervention programs.

Women and Artisanal Fishing in the Quilombola Community of Santiago do Iguape, Bahia: Historical Contributions and Current Challenges

Objective: To analyze the contributions of female fishers to the preservation of knowledge about local artisanal fishing, as well as the challenges they face in occupying these spaces. Introduction and Theoretical Framework: Data on the importance of artisanal fishing is presented, highlighting its relevance in the intergenerational transmission of this knowledge by women. It also emphasizes the neglect and invisibility faced by women throughout history due to gender issues, which led to women achieving basic rights granted to "fishermen" only belatedly. Method: The methodology adopted includes field data collection through semi-structured interviews with female fishers from the community, as well as direct observations. The interviews were conducted using the snowball sampling method, as described by Bailey (1994). The interviews were recorded and accompanied by photographic records, with proper authorization obtained through the signing of the Informed Consent Form (ICF), which was read and explained to each participant. Results and Discussion: The results show that female fishers possess extensive knowledge about fishing techniques and equipment, fishing resources, and other environmental issues. These women face a triple workload and many difficulties in estuarine environments. They recognize the sea and mangroves as prosperous areas that allow them to raise their children and obtain resources for their subsistence. Fishing becomes more than just an economic activity; it shapes the identity and ways of being/living/inhabiting of these women. Thus, the quilombola women of Santiago do Iguape take on a leading role in an activity marked by gender issues and the pursuit of basic rights. Implications of the Research: The research contributes to the recognition of fishing knowledge built by female fishers. These discussions may contribute to the improvement and implementation of new policies that address the current vulnerabilities faced by these fishers. Originality/Value: This study is essential for highlighting social and governmental invisibility due to gender issues, as well as the changes in women’s self-perception regarding their importance in the construction and preservation of knowledge about artisanal fishing and their rights.

Enhancing Smart Healthcare Networks: Integrating Attribute-Based Encryption for Optimization and Anti-Corruption Mechanisms

This study investigates the feasibility and effectiveness of integrating Attribute-Based Encryption (ABE) into smart healthcare networks, with a particular focus on its role in enhancing anti-corruption mechanisms. The study provides a comprehensive analysis of current vulnerabilities in these networks, identifying potential data security risks. An anti-corruption mechanism is designed to ensure data integrity and reliability. The ABE approach is then empirically compared to other prominent encryption algorithms, such as Identity-Based Encryption, Data Encryption Standard, Advanced Encryption Standard, and Rivest-Shamir-Adleman algorithms. These methods are evaluated based on access latency, data transmission speed, system stability, and anti-corruption capabilities. Experimental results highlight the strengths of the ABE algorithm, demonstrating an average access latency of 31.6 milliseconds, a data transmission speed of 3.56 MB/s, and an average system stability of 98.74%. Furthermore, when integrated into anti-corruption mechanisms, ABE effectively protects against data tampering and misuse, ensuring secure data transmission. Compared to alternative algorithms, ABE offers a more efficient, secure, and stable solution for data management within smart healthcare networks, supported by its robust anti-corruption capabilities. This positions ABE as an optimal choice for safeguarding the integrity and security of healthcare data.

Developing a multi-level european-wide composite indicator to assess vulnerability dynamics across time and space

The escalating frequency of extreme climatic events and ongoing urbanisation expose European communities to increasing disaster risks, which are determined not only by the hazardous events themselves, but also by the exposure and vulnerability to these hazards. Consequently, effective risk management strategies cannot overlook a comprehensive understanding of the factors influencing vulnerability of the communities. This paper addresses this need by presenting a European-wide framework for the development of a Vulnerability Index (VI) that evaluates vulnerability at both national and subnational scales. Adopting a multi-dimensional and multi-level approach, the VI captures socio-economic, political, environmental, and physical factors contributing to community resilience. A standardised, supranational methodology is employed, providing harmonised cross-country information and time series data for vulnerability and its underlying indicators. This comprehensive assessment facilitates the understanding of socio-economic dynamics, enabling the formulation of targeted policy actions at both country and subnational levels. By offering insights into current vulnerability trends, the VI underlines the importance of governance, economic factors, and disaster preparedness in reducing vulnerability at different administrative levels, while highlighting the role of social factors, such as poverty and social exclusion, in community vulnerability at sub-regional levels.

Mobilizing Evidence-based Knowledge for Sustainable Wetlands Co-management and Co-governance amidst increasing Anthropogenic and Environmental Stressors: Key Lessons from Mityana District, Uganda

Wetlands (covering about 1.5–1.6 billion hectares globally), are critical biodiversity and livelihood hotspots. Wetlands further replenish the global economy with $47.4 trillion/year worth of ecosystem services. By jealously guarding wetlands, progress toward sustainable development goals, and livelihood welfare are possible. Unfortunately, despite the promulgation of wetland governance mechanisms, 35 percent of the global natural wetlands have been lost since the 1970s. This could be worse in undocumented or explored wetland zones situated in remote tropical regions. In this study, we bring to the fore insights from 286 documents sourced from Scopus and engagements from 105 citizens in Mityana, to (i) map wetlands (including the current vulnerabilities and threats), and (ii) co-develop a wetlands management action pathway that could create sustainable co-management possibilities and sustainable livelihood futures. Findings revealed that although research on wetlands has increased for the last 31 years, since 2021, it has plummeted. In Uganda, wetland research and scholarship is predominantly situated around the Lake Victoria region. Most research focuses on natural or biological sciences. Emerging policy themes and trending research topics are shifting from key wetland management paradigms. From a total of 105 sampled wetlands scattered across fourteen (14) sub-counties in the Mityana district, critical wetland issues were unraveled. Mityana is crossed by two wetland systems (Lake Wamala and River Mayanja dominated by permanent papyrus and seasonal swamps respectively. Wetlands offer unique livelihood, cultural assets/capitals, and ecological benefits (including cultural/aesthetics meaning). An unfathomable rate of degradation is evident. Anthropogenic factors are the predominant threat drivers, especially eucalyptus planting. The loss of culturally valuable wetlands has increased socio-cultural-ecological grief, such as around Lake Wamala. Micro-level management actions are increasing, albeit mainly around accessible permanent wetlands. Most riparian wetland sedentary populations expressed willingness and interest in the co-management and governance of community wetlands. More robust actions and pathways are needed to create avenues for community co-management. The co-developed the sustainable wetlands management action pathway (SWeMAP) provides seven (7) coherent steps, including critical social science insights that could aid sustainable wetlands governance and management across geographies. As wetlands in Uganda have been gazetted as critical to sustainable development, the urgent co-development and financing of micro-level wetland action plans, including situational inventories could help create avenues for sustainable wetlands management.

Urban Vulnerability Assessment of Sea Level Rise in Singapore through the World Avatar

This paper explores the application of The World Avatar (TWA) dynamic knowledge graph to connect isolated data and assess the impact of rising sea levels in Singapore. Current sea level rise vulnerability assessment tools are often regional, narrow in scope (e.g., economic or cultural aspects only), and are inadequate in representing complex non-geospatial data consistently. We apply TWA to conduct a multi-perspective impact assessment of sea level rise in Singapore, evaluating vulnerable buildings, road networks, land plots, cultural sites, and populations. We introduce OntoSeaLevel, an ontology to describe sea level rise scenarios, and its impact on broader elements defined in other ontologies such as buildings (OntoBuiltEnv ontology), road networks (OpenStreetMap ontology), and land plots (Ontoplot and Ontozoning ontology). We deploy computational agents to synthesise data from government, industry, and other publicly accessible sources, enriching buildings with metadata such as property usage, estimated construction cost, number of floors, and gross floor area. An agent is applied to identify and instantiate the impacted sites using OntoSeaLevel. These sites include vulnerable buildings, land plots, cultural sites, and populations at risk. We showcase these sea level rise vulnerable elements in a unified visualisation, demonstrating TWA’s potential as a planning tool against sea level rise through vulnerability assessment, resource allocation, and integrated spatial planning.

Climate change ecological vulnerability and hotspot analysis of himalayan forests in North-Eastern region, India

The Himalayan forests are vulnerable to climate change leading to disturb the current flow of critical ecosystem services to the dependent population. Present study attempts to evaluate the current vulnerability status of major forest types in Nagaland, India due to climate change along with identifying the hot spots for mitigating the vulnerability of the forests. Vulnerability of mixed moist deciduous, pine, wet hill and wet temperate forests were evaluated using the IPCC framework. Local Moran's I analysis, hot spot analysis and a histogram analysis of the vulnerability were made in QGIS. Field data such as Shannon-Wiener Index and Importance Value Index along with secondary data such as edaphic factors, vegetation factors and climatic variables were used for vulnerability analysis. Analysis results that mixed moist deciduous forests had the highest area in under high-high clusters, hot spots and was highly vulnerable. The result suggests that very dense or moderately dense forest cover were less vulnerable than low density forests in the region. The study provides baseline information along with identification of vulnerable hot spot forests for future climate change policy and management of resources at the division level. The study suggests strengthening the less dense forests along with increasing the biodiversity through suitable strategy for mitigating the vulnerability.

Obstacles and countermeasures for protecting Internet of Things devices from emerging security risks

The rapid proliferation of Internet of Things (IoT) devices has ushered in a paradigm shift, revolutionising the way we interact with and perceive our environment. This phenomenon has given rise to a hyper-connected ecosystem, seamlessly integrating smart devices into the fabric of homes, cities and industries. While this interconnectedness holds tremendous promise for enhancing efficiency and convenience, it concurrently exposes a complex web of security challenges. This paper delves into the intricate interplay between the expansive scope of IoT deployment and the challenges it poses to security practitioners, policymakers and technology developers alike. By critically assessing current security gaps and potential weaknesses in IoT infrastructures, the research identifies key areas of vulnerability, ranging from insecure communication protocols and inadequate device authentication to insufficient data encryption. In response to these identified challenges, the paper proposes a set of innovative and pragmatic countermeasures aimed at mitigating emerging threats to IoT security. Emphasising the importance of a holistic security framework, the suggested countermeasures span technological enhancements, policy interventions and user education initiatives. The goal is to establish a resilient security posture that not only addresses current vulnerabilities but also adapts to the evolving threat landscape, thereby fostering a more secure and trustworthy IoT ecosystem. Through this research, we aim to contribute valuable insights to the ongoing discourse on IoT security, fostering a deeper understanding of the intricate dynamics at play and providing actionable recommendations for stakeholders invested in fortifying the security foundations of our increasingly interconnected world.

Homeowners’ financial vulnerability over the house price cycle

Abstract This paper investigates the financial vulnerability dynamics of indebted homeowners over the housing cycle using an agent-based housing market model, calibrated with UK microdata. The findings suggest that financial vulnerability is primarily driven by house purchases and dissaving due to a wealth effect on consumption. The former is more important during house price upswings, while the latter becomes significant at high price levels. Additionally, current vulnerability is path-dependent on previous purchases at high prices, as these purchases, due to a wealth effect, result in temporarily elevated consumption and consequently reduced financial buffers.

So How Did We Get Here? A Historical Case Study of Migrant Employment in the New Zealand Hotel Sector

This article maps the transition from a corporatist to a neoliberal consensus in the hotel industry in New Zealand, focussing on the changing labour conditions for migrant workers. We show how the current vulnerabilities for migrant workers, such as poor pay and conditions, and low unionisation, came into being. While much “presentist” research takes migrant worker vulnerability in hospitality and tourism for granted, this article finds that migrant workers did not always experience such vulnerability but, rather, this was constructed over time. The impacts of employment legislation and ownership changes during the 1980s and 1990s were crucial. By taking a critical historical employment relations approach, we better contextualise the current moment of labour shortages, reliance on migrant labour and by “race to the bottom” employment conditions. This suggests that the drive for sustainable employment practices will remain “aspirational” until the power imbalance in New Zealand employment relations is addressed.

Quantum Key Distribution. A survey on current vulnerability trends and potential implementation risks.

Quantum Key Distribution. A survey on current vulnerability trends and potential implementation risks.

Software installation threat detection based on attention mechanism and improved convolutional neural network in IOT platform

With of the Internet of Things (IoT) developing and the network technique progressing, malware attacks continue to occur, seriously endangering the information and property security of Internet of Things device users. To ensure the security of the Internet of Things platform and improve the efficiency of malware and vulnerability detection, a software installation threat detection model based on attention mechanism and improved convolutional neural network is constructed. Firstly, the enhanced dynamic symbolic execution module and forward program slicing algorithm are used to extract dynamic features, and then the improved convolutional neural network is utilized to classify malware. In the existing software of IoT devices, the inlining correlation function is studied using the inlining strategy, and the weight between the target pixel and the global pixel is calculated using the attention mechanism, through which the logic and correlation between the triples are correlated. Then, deep residual network is used to detect software vulnerabilities. This enables threat detection before and after software installation. In comparison with the current popular vulnerability detection model experiments, the accuracy, recall rate, accuracy rate and running time of the constructed model in the process of vulnerability detection are 0.975, 0.970, 0.968 and 0.02 s, respectively. Compared with other models, the research design model has better performance. This shows that this built model can effectively detect software installation threats, and has high detection accuracy and operation efficiency, which can provide strong support for the Internet of Things platform’s security protection.

Analysis of Flood Disaster Resilience in Kroya District Indonesia Year 2024

This research was conducted to analyze the level of flood disaster resilience in Kroya District, Cilacap Regency in 2024 at the household level. This writing was designed as a qualitative and quantitative research model with case studies to determine how adaptation efforts function to reduce the level of vulnerability. So it is expected that there will be a difference between current vulnerabilities and future vulnerabilities. This difference is called resilience, which in this study will be explained at the household level. This research used a survey approach to obtain data from the people of Bunju Village and Mujur Village in Kroya District, Cilacap Regency. The results of the research show that the average resilience level results of Buntu Village and Mujur Village are categorized as high resilience, Buntu Village with a resilience level value of 0.695 (research value conversion) and Mujur Village with a resilience level value of 0.721 (research value conversion). So it can be concluded that the people of these two areas are ready to face the danger of a flood disaster if it occurs.

IoT Device Security and Network Protocols: A Survey on the Current Challenges, Vulnerabilities, and Countermeasures

IoT Device Security and Network Protocols: A Survey on the Current Challenges, Vulnerabilities, and Countermeasures