Vulnerability Assessment Research Articles

Process Systems Engineering for Climate-Resilient Infrastructure: A Framework for Vulnerability Assessment and Optimization

This study explores the application of Process Systems Engineering (PSE) methodologies to enhance the climate resilience of infrastructure systems. As climate change increasingly challenges infrastructure, traditional designs often fail to address evolving long-term risks, leading to system vulnerabilities. PSE techniques, including vulnerability assessments, optimization models, sensitivity analysis, and scenario planning, offer a structured approach to identify weaknesses, assess adaptation strategies, and inform decision-making for climate-resilient infrastructure. Through a synthesis of existing research and case studies from energy, transportation, and water sectors, this study highlights the effectiveness of PSE methods in quantifying infrastructure vulnerabilities under various climate projections. Key findings show that investing in adaptive measures, such as upgrading energy storage systems and flood prevention infrastructure, provides long-term cost savings and resilience improvements. Despite challenges like data gaps and high uncertainty, the study demonstrates that PSE frameworks can significantly improve infrastructure design and planning, helping decision-makers develop strategies that are both cost-effective and adaptive to climate change.

Risk analysis and protection in case of intrusion of nuclear facilities

Abstract Physical protection systems (PPSs) are designed to counter and neutralize any theft or sabotage attempts carried out against a given site. PPS designs are crucial, requiring rigorous analysis and evaluation to ensure their reliability, sustainability and optimal security. This paper assumes a Hypothetical Nuclear Research Center (HNRC) for PPS analysis and evaluation. This work will determine the PPS’s most vulnerable path elements, by demonstrating expected intrusion attack scenarios by taking advantage of the HNRC’s design weaknesses. Also, this work determines the threats resulting from adversary intrusion through the weakness path elements located at the nuclear site. Additionally, this paper develops an analytical methodology for this evaluation and risk assessment, by using the Systematic Analysis of Vulnerability to Intrusion (SAVI) computer program. Through constructing adversary sequence diagrams (ASDs), SAVI can easily identify the HNRC’s most vulnerable paths, pinpointing the areas which require the most attention. Alongside SAVI is the quantitative risk analysis method - the Dai et al. Model – which can calculate the effectiveness and risk of the PPS itself by measuring its degree of uncertainty using effectiveness entropy. To comply with effectiveness and risk standards, this work also introduces security system upgrade processes and determines the optimal security solution for the HNRC.

A Practical Human-Centric Risk Management (HRM) Methodology

Various standards (e.g., ISO 27000x, ISO 31000:2018) and methodologies (e.g., NIST SP 800-53, NIST SP 800-37, NIST SP 800-161, ETSI TS 102 165-1, NISTIR 8286) are available for risk assessment. However, these standards often overlook the human element. Studies have shown that adversary profiles (AP), which detail the maturity of attackers, significantly affect vulnerability assessments and risk calculations. Similarly, the maturity of the users interacting with the Information and Communication Technologies (ICT) system in adopting security practices impacts risk calculations. In this paper, we identify and estimate the maturity of user profiles (UP) and propose an enhanced risk assessment methodology, HRM (based on ISO 27001), that incorporates the human element into the risk evaluation. Social measures, such as awareness programs, training, and behavioral interventions, alongside technical controls, are included in the Human-Centric Risk Management (HRM) risk treatment phase. These measures enhance user security hygiene and resilience, reducing risks and ensuring comprehensive security strategies in SMEs.

PUF-Dilithium: Design of a PUF-Based Dilithium Architecture Benchmarked on ARM Processors

Addressing the looming threat posed by quantum computers capable of breaching current public key cryptography schemes has become imperative. To this end, the National Institute of Standards and Technology (NIST) initiated a competition in Post-Quantum Cryptography (PQC), resulting in the selection of four schemes as the new standardized replacements, while a fourth round and an additional signature round is still ongoing. Notably, CRYSTALS-Dilithium, a lattice-based signature scheme, has exhibited promising resilience due to its efficiency and simplicity. Despite the finalization of standardization for these new four schemes, transitioning from classical cryptography to these alternatives necessitates further investigation and analysis. Comprehensive scrutiny of these newly standardized schemes is imperative, including considerations of implementation efficiency across various platforms and side-channel vulnerability analysis. This paper introduces a novel design leveraging physical unclonable functions (PUFs) to bolster the physical security of CRYSTALS-Dilithium. Physical security is paramount in scenarios where network nodes are exposed to public scrutiny, potentially making them targets for adversaries. After discussing the advantages of our design compared to the original design, we implemented it on two different architectures, ARMv7 and ARMv8. Our results indicate substantial improvements in both security and performance compared to existing references. Moreover, noting the new competition initiated by the NIST in 2023 for new signatures (first round finalized in October 2024), potentially the proposed schemes can be adopted to the new standards set to be finalized in the coming years. These make our scheme not solely confined to the current standards and would be an important merit of the presented approaches.

Comparative study of DRASTIC-LU and radioactive isotope approaches for assessing groundwater vulnerability to pollution: the case study of Abuja, North Central Nigeria

Groundwater resources in Abuja, North Central Nigeria, are facing increasing vulnerability to pollution due to urbanization and anthropogenic activity. There are several methods of assessing groundwater vulnerability to contamination. Choosing the appropriate method for the study site, which is paramount for accurate vulnerability assessment, is sometimes very tasking. The DRASTIC-LU and 3H radioactive tracer methods were assessed in this study and applied to the Abuja aquifers. Water scientists have widely adopted these methods in vulnerability assessments. From the final DRASTIC-LU vulnerability map, it was observed that high to very high vulnerability areas were located in southwestern and northeastern parts of the area. 33% of the wells in the entire area exceed the nitrates statutory limits for drinking water, while 87% of the wells exceeding the nitrates statutory limits were located in high to very highly vulnerable areas. The radioactive tracers provided information on an Abuja aquifer-wide basis, showing areas of most recent recharge (post-nuclear) and older recharge (pre-nuclear), respectively. With the tracer approach, areas of preferential flow and diffuse flow indicating high vulnerability and low vulnerability, respectively, were mapped. This systematic review discusses in detail the advantages and limitations of these methods employing the origin-pathway-target model of vulnerability assessments as the basics of the study. Finally, the application of a dual approach involving the combination of the two is best for vulnerability assessments. This study therefore proposes the need for policymakers to adopt combined methodological approaches for sustainable groundwater management.

Decadal evolution of GIS in disaster management and risk assessment

This study conducts a bibliometric analysis of the evolution of Geographic Information Systems (GIS) in disaster risk management and assessment over a 25-year period, from 2000 to 2024. Utilizing a dataset derived from academic publications indexed in prominent scientific databases, we examine the growth trajectory, thematic evolution, scholarly collaboration, and technological advancements within the field. Our findings reveal a significant increase in the volume of GIS-related research in disaster management, underscored by a shift from foundational applications toward the integration of cutting-edge computational techniques. Analysis of collaboration networks highlights the global nature of research efforts, demonstrating extensive international cooperation that transcends geographical and disciplinary boundaries. Thematic analysis indicates a progressive focus on vulnerability assessments, climate change impacts, and the incorporation of remote sensing and machine learning technologies, reflecting the field's response to emerging challenges and the dynamic landscape of disaster risk management. The study not only charts the historical development of GIS applications in this domain but also identifies key research trends, influential works, and potential future directions, underscoring the critical role of GIS in enhancing disaster resilience. This bibliometric perspective provides valuable insights into the maturation of GIS as an indispensable tool in disaster management and offers a roadmap for future research and technological innovation aimed at mitigating disaster risks and building resilient communities

Criticality disaster risk assessment for urban rail transport in Indonesia

The increasing frequency of extreme weather events due to climate change poses significant risks to urban rail systems, especially in disaster-prone regions like Indonesia. Urban railways, with limited rerouting options, are highly vulnerable to natural disasters such as floods, landslides, and earthquakes. These disruptions can cause cascading economic impacts, including infrastructure damage, productivity loss, and prolonged travel times. This study develops a methodological framework to assess disaster risk and climate vulnerability in urban rail systems, with Bandung, Indonesia, as the case study. The framework integrates Climate Vulnerability and Risk Assessment (CVRA) with the Movement and Place (M&P) framework, leveraging Geographic Information System (GIS) technology to identify and prioritize high-risk areas. CVRA evaluates hazards, exposure, and vulnerabilities, while M&P assesses the functional significance of transport nodes based on movement patterns and land use density. The combined analysis produces a risk matrix, enabling targeted mitigation strategies that integrate engineering solutions, urban planning, and policy interventions. Findings highlight critical vulnerabilities in Bandung’s proposed LRT system, particularly at stations susceptible to earthquakes and landslides. Recommended mitigation measures include resilient infrastructure designs, strategic planning for high-risk zones, and stakeholder engagement for prioritization. This framework offers practical guidance for policymakers to enhance urban rail resilience, reduce climate-related risks, and ensure sustainable urban mobility. It serves as a scalable model for other cities in Indonesia and globally, supporting adaptive and sustainable transport systems.

A proposal to measure the resilience of the Andalusian Commnunity Social Services

Introduction. The COVID-19 pandemic shed light on the weaknesses of social services directed towards the most vulnerable populations. A robust social services framework is, thus, necessary to mitigate the impact of the crisis. In this work, a resilience index is advanced based on the capacities of social services to buffer and alleviate the adverse effects of crises, including the recent pandemic. Thus, the study’s objective was to create a resilience index based on accessible data to assess the extent to which Andalusia’s social services were capable of mitigating the effects of the pandemic. Methodology. A novel methodology, the HVCRA (Hazard, Vulnerability, Risk, and Capacity Analysis), is introduced in this paper. Though traditionally used to assess natural disasters, HVCRA was applied here to gauge the pandemic's impact on social services. To develop the index, expert validation was conducted through the Delphi method, stakeholder evaluation, and the calculation of pre- and post-pandemic resilience indices for municipalities in Andalusia (an autonomous region in southern Spain). Results. The study unfolded in three phases: identification of resilience indicators, data selection, and index calculation. High modal values were obtained with the Delphi method, and significant variables were identified in stakeholder focus groups. The applicability of the final index, reduced to 17 indicators, could be improved through ongoing contextualisation efforts. Discussion. Critical indicators to assess social service resilience were put forward, in line with the research conducted by Kruk et al. who propose a resilience index for healthcare. Structural indicators, such as budget allocation and personnel, play pivotal roles, though data availability challenges persist, particularly in municipalities with over 20,000 inhabitants. Despite the study’s limitations, the proposed indicators are promising in terms of offering a comprehensive resilience assessment method directed towards community social service systems. Conclusions. The study establishes a robust framework for evaluating community social service resilience, although data accessibility remains a challenge. While acknowledging the study’s limitations, the proposed indicators lay the groundwork for attaining a comprehensive evaluation in the future, underscoring the imperative of addressing data availability in order to achieve a more nuanced assessment of social service resilience.

Comparative analysis of EPIK, DRASTIC, and DRASTIC-LUC methods for groundwater vulnerability assessment in karst aquifers of the Western Amazon Basin

Comparative analysis of EPIK, DRASTIC, and DRASTIC-LUC methods for groundwater vulnerability assessment in karst aquifers of the Western Amazon Basin

Spatiotemporal analysis of future drought vulnerability in the Hindu Kush Region: A case study of the Karnali River Basin

Spatiotemporal analysis of future drought vulnerability in the Hindu Kush Region: A case study of the Karnali River Basin

Analysis of vulnerability, its drivers, and strategies applied towards reducing the pastoral and agro-pastoral livelihood vulnerability to climatic shocks

In recent decades, the global climate has changed mainly due to human-induced causes and realizing their manifestations in the forms of extreme events such as droughts, floods, heat stress, and variability in rainfall. Arid and semi-arid ecosystems are sensitive to changes in climate variability, including the Borana zone. This study was therefore initiated to assess how vulnerable pastoral and agro-pastoral livelihoods are to climate change, as well as to estimate the effects, and pinpoint potential response measures that could be implemented in the study area. Data were gathered by surveys, focused group and expert group discussions. The quantitative data were analyzed through descriptive and inferential statistics, while the qualitative data was analyzed using thematically organized content analysis. The findings indicate that there is high degree of climatic risk to the livelihoods of both pastoralists and agro-pastoralists (− 0.37). The ability of pastoralists to adapt in comparison to agro-pastoralists is largely determined by numbers of factors, including inadequate livelihood strategies, poor access to social safety networks and services, knowledge and communication gaps, and availability of water resources. The area was extremely susceptible to the effects of climate change, which led to disaster. The primary outcome, which also affects other sources of income, is the loss of livestock (97%) which is followed by food shortages (91%), decreased income (84%), feed scarcity (83%), water scarcity (80%), and crop failure (79%). Managing livestock, taking advantage of social capital, storing hay and crop residue, and destocking animals during the period of severe drought were the main strategies used to reduce the vulnerability and enhance the adaptive capacity. Furthermore, despite the government’s numerous efforts to lesson enduring vulnerabilities and their effects, progress has not been encouraging because of lack of proactive action when faced with emergences. Hence, in order to decrease vulnerability and increase adaptive capacity, policymakers and development practitioners should collaborate proactively and develop area-specific adaptation strategies. These might include income diversification, increased access to water and pasture; installation of easily accessible market channels; and establishment of early warning systems that assist community preparation and resilience.

Harnessing complexity: integrating remote sensing and fuzzy expert system for evaluating land use land cover changes and identifying mangrove forest vulnerability in Bangladesh

Purpose: This study analyzes Landsat images to examine the alterations in land cover within the Sundarbans and its surrounding regions in Bangladesh, spanning twenty-one years from 2000 to 2021. Furthermore, we develop a mangrove vulnerability map considering the combined effect of eight socioeconomic, geophysical, and climatic factors. Methods: Land use land cover (LULC) changes in the study area over a 21-year period were assessed using a random forest model, and the vulnerability analysis employed a fuzzy expert-based multicriteria decision-making (MCDM) approach. Results: The results show that a significant portion of the mangrove forest has been transformed into aquaculture practices because of the expansion of high-value shrimp cultivation. A decrease in forest areas and the expansion of aquaculture zones suggest a livelihood shift among the local population over time. This transition has adversely affected human activities within the ecosystem and the biodiversity of mangrove forests. Consequently, it is imperative to implement suitable measures to enhance the state of mangrove forests and safeguard their biodiversity. The vulnerability analysis shows that the highly vulnerable, moderately vulnerable, and low vulnerable areas cover 35.66%, 26.86%, and 19.42%, respectively. Conclusion: The vulnerability maps generated in this research could serve as a valuable resource for coastal planners seeking to ensure the sustainable stewardship of these coastal mangrove forests. These results offer a detailed understanding of coastal mangrove LULC patterns and vulnerability status, which will be useful for policymakers and resource managers to urgently incorporate into coastal land use and environmental management practices.

Population Genomics Reveals Local Adaptation Related to Temperature Variation in Two Stream Frog Species: Implications for Vulnerability to Climate Warming.

Identifying populations at highest risk from climate change is a critical component of conservation efforts. However, vulnerability assessments are usually applied at the species level, even though intraspecific variation in exposure, sensitivity and adaptive capacity play a crucial role in determining vulnerability. Genomic data can inform intraspecific vulnerability by identifying signatures of local adaptation that reflect population-level variation in sensitivity and adaptive capacity. Here, we address the question of local adaptation to temperature and the genetic basis of thermal tolerance in two stream frogs (Ascaphus truei and A. montanus). Building on previous physiological and temperature data, we used whole-genome resequencing of tadpoles from four sites spanning temperature gradients in each species to test for signatures of local adaptation. To support these analyses, we developed the first annotated reference genome for A. truei. We then expanded the geographic scope of our analysis using targeted capture at an additional 11 sites per species. We found evidence of local adaptation to temperature based on physiological and genomic data in A. montanus and genomic data in A. truei, suggesting similar levels of sensitivity (i.e., susceptibility) among populations regardless of stream temperature. However, invariant thermal tolerances across temperatures in A. truei suggest that populations occupying warmer streams may be most sensitive. We identified high levels of evolutionary potential in both species based on genomic and physiological data. While further integration of these data is needed to comprehensively evaluate spatial variation in vulnerability, this work illustrates the value of genomics in identifying spatial patterns of climate change vulnerability.

Seismic and Tsunamis Vulnerability Assessment of the Shelter School Building Structure with and without Retrofitting

Seismic and Tsunamis Vulnerability Assessment of the Shelter School Building Structure with and without Retrofitting

Hacking Exposed: Leveraging Google Dorks, Shodan, and Censys for Cyber Attacks and the Defense Against Them

In recent years, cyberattacks have increased in sophistication, using a variety of tools to exploit vulnerabilities across the global digital landscapes. Among the most commonly used tools at an attacker’s disposal are Google dorks, Shodan, and Censys, which offer unprecedented access to exposed systems, devices, and sensitive data on the World Wide Web. While these tools can be leveraged by professional hackers, they have also empowered “Script Kiddies”, who are low-skill, inexperienced attackers who use readily available exploits and scanning tools without deep technical knowledge. Consequently, cyberattacks targeting critical infrastructure are growing at a rapid rate, driven by the ease with which these solutions can be operated with minimal expertise. This paper explores the potential for cyberattacks enabled by these tools, presenting use cases where these platforms have been used for both offensive and defensive purposes. By examining notable incidents and analyzing potential threats, we outline proactive measures to protect against these emerging risks. In this study, we delve into how these tools have been used offensively by attackers and how they serve defensive functions within cybersecurity. Additionally, we also introduce an automated all-in-one tool designed to consolidate the functionalities of Google dorks, Shodan, and Censys, offering a streamlined solution for vulnerability detection and analysis. Lastly, we propose proactive defense strategies to mitigate exploitation risks associated with such tools, aiming to enhance the resilience of critical digital infrastructure against evolving cyber threats.

Quantifying household vulnerability to power outages: Assessing risks of rapid electrification in smart cities

As cities accelerate decarbonization through building electrification, the growing dependence on electrical systems introduces new vulnerabilities during power disruptions. While grid-level resilience has been widely studied, household-scale impacts of electrification remain poorly understood. In this study, we develop a vulnerability assessment framework that combines machine learning classification with high-resolution synthetic energy data from 129,000 U.S. single-family homes. Our two-stage approach first identifies household electrification levels with over 80% accuracy and then quantifies outage vulnerability using a composite risk index that incorporates electrification profiles, backup capabilities, and climate exposure. A simulated case study reveals that fully electrified households face significantly higher risks during winter storms, with a 60% greater vulnerability compared to mixed-energy homes. In contrast, solar-equipped electrified households exhibit enhanced resilience during heat waves, leveraging renewable energy resources to mitigate risks. By highlighting critical dependencies and adaptive capacities, our framework emphasizes the importance of energy diversity and distributed energy resources in reducing outage vulnerabilities. This scalable, non-intrusive methodology provides actionable insights for policymakers and urban planners to design climate-resilient urban energy systems.

Assessing changing baleen whale distributions and reported incidents relative to vessel activity in the Northwest Atlantic.

Baleen whales are among the largest marine megafauna, and while mostly well-protected from direct exploitation, they are increasingly affected by vessel traffic, interactions with fisheries, and climate change. Adverse interactions, notably vessel strikes and fishing gear entanglement, often result in distress, injury, or death for these animals. In Atlantic Canadian waters, such negative interactions or 'incidents' are consistently reported to marine animal response organizations but have not yet been analyzed relative to the spatial distribution of whales and vessels. Using a database of 483,003 whale sightings, 1,110 incident reports, and 82 million hours of maritime vessel activity, we conducted a spatiotemporal vulnerability analysis for all six baleen whale species occurring in the Northwest Atlantic Ocean by developing an ensemble of habitat-suitability models. The relative spatial risk of vessel-induced incidents was assessed for present (1985-2015) and projected near-future (2035-2055) distributions of baleen whales. Areas of high habitat suitability for multiple baleen whale species were intrinsically linked to sea surface temperature and salinity, with multispecies hotspots identified in the Bay of Fundy, Scotian Shelf, Laurentian Channel, Flemish Cap, and Gulf of St. Lawrence. Present-day model projections were independently evaluated using a separate database of acoustic detections and found to align well. Regions of high relative incident risk were projected close to densely inhabited regions, principal maritime routes, and major fishing grounds, in general coinciding with reported incident hotspots. While some high-risk regions already benefit from mitigation strategies aimed at protecting North Atlantic Right Whales, our analysis highlights the importance of considering risks to multiple species, both in the present day and under continued environmental change.

Utilizing Remote Sensing and GIS to Study Natural Disasters "Volcanoes" and Their Impact on Climate Change

Multifarious regions around the world are exposed to natural hazards and disasters, each with unique characteristics. A higher frequency of extreme hydro-meteorological events, most probably related to climate change, and an increase in vulnerable population have been addressed as potential causes of such disasters. To mitigate the consequences of these disasters, Disaster Risk Management, including hazard assessment, elements-at-risk mapping, vulnerability and risk assessment of spatial components as well as Earth Observation (EO) products and Geographic Information Systems (GIS), should be considered. Multihazard assessment entails the evaluation of relationships between various hazards, including interconnected or cascading events, as well as focusing on various levels from global to local community levels, as each level manifests particular objectives and spatial data. This paper presents an overview of the diverse types of spatial data and explores the methods applied in hazard and risk assessments, with volcanic eruptions serving as a specific example. The rapid development of scientific research and the advancement of Earth Observation satellites in recent years have revolutionized the concepts of geologists and researchers. These satellites now play an indispensable role in supporting first responders during major disasters. The coordination of satellite deployment ensures a swift response along with allowing for the timely delivery of critical images. In tandem, remote sensing technologies and geographic information systems (GIS) have emerged as essential tools for geospatial analysis. The application of remote sensing and GIS for the detection of natural disasters was examined through a review of academic papers, offering an analysis of how remote sensing is utilized to assess natural hazards and their link to climate change.

Insider Threats: The Cybersecurity Analysis using OCTAVE Allegro which are combined with HAIS-Q

There are various types of cybersecurity threat in the globe, one of which is an insider threat. Because the current vulnerability generates an insider threat, SMEs suffer. In this situation, the company suffers a loss of profit and trust. Because of the speed and intensity of cybersecurity, particularly internal threats, SMEs must conduct regular vulnerability assessments. Insider threats to cyber security are a major issue in today's environment. Insider threats come in a variety of flavours, one of which is the unintended insider threat, or UIsT. This type of threat is a real one, and it is important to understand who and how they can become an insider threat.

Exploring the Role of Location-Based Games in Managing Tourist Destinations Under Climate Change Challenges: A Gap Analysis Review

Global climate disruptions pose escalating threats to tourism networks, necessitating innovative resilience solutions tailored for regional interdependencies. This review examines research on location-based games for enhancing climate resilience across interconnected tourism economies. Analyzing 75 studies, strengths and limitations are delineated. While confirming augmented reality, virtual reality, and geo-tagging versatility for promotion, analysis, and experience enhancement, findings reveal gaps in leveraging these technologies for systemic coordination, participatory governance, embodied vulnerability assessment, and social learning. Immersive climate visualizations, policy simulations, and multiplayer interfaces emerge as frontiers enabling collaborative adaptation. The top priorities are (1) integrating localized climate projections with human perceptions through interactive visualizations to create tangible threats, (2) designing policy simulations for participatory governance of resilience investments across sectors, (3) developing embodied social learning vulnerability assessments highlighting differential exposures, and (4) designing multiplayer games to facilitate the co-creation of equitable, robust adaptation strategies by communities. Targeted research advancing location-based platforms to link science, policy, and community priorities is essential for tourism networks to navigate intensifying climate disruptions collaboratively. This review thus delineates critical next steps in utilizing geo-technologies’ participatory, experiential promise to inform and connect stakeholders in steering tourism toward resilient pathways.