Vulnerability Assessment Research Articles

Modal-Based Fragility Analysis of High-Rise Tubular Structures: A Methodology for Vulnerability Assessment

This study addresses the limitations of current vulnerability assessment processes for tall buildings, which fail to incorporate the effects of higher modes and the resulting structural vulnerability to seismic hazards. Additionally, the extensive computational resources required for assessing tubular high-rise buildings make vulnerability assessments almost impossible. This study proposes a new methodology for assessing the modal-based structural vulnerability of high-rise reinforced concrete (RC) tubular buildings by incorporating nonlinear response and reducing computational effort. The proposed methodology discreetly develops the vulnerability information of each structural vibrational mode separately using nonlinear time history analysis rather than the linear Modal Response Spectrum Analysis (MRSA). The methodology includes steps for establishing vulnerability information for high-rise tubular buildings, and a case study of a 55-story RC building with core wall is presented to demonstrate the methodology. The vibrational modes of the building were decoupled and analyzed separately using single degree of freedom (SDOF) systems, and fragility curves were developed for three different limit states using various intensity measures. The obtained fragility relationships were compared with the curves of another structure of similar class. The results indicated good compatibility and significance of incorporating higher vibrational modes in assessment of structural vulnerability, thus, proposed methodology can be extended to any structural configuration of tubular buildings.

Building typology classification using convolutional neural networks utilizing multiple ground-level image process for city-scale rapid seismic vulnerability assessment

Several studies have focused on generating seismic vulnerability maps for earthquake-prone areas, particularly in Indonesia. Building typologies are a key factor in determining vulnerability to earthquakes. However, conducting large-scale field surveys to determine the spatial distribution of building typologies in a city is uneconomical. This paper explores the use of a convolutional neural network (CNN) to automatically detect building typologies from diverse regions in Indonesia, utilizing both conventional and automated building image acquisition processes. In this study, datasets from three distinct image acquisition methods are trained with four unique CNN architectures to identify the best-performing model to classify building typologies. The sample size effect on CNN performance is also investigated. The results showed that randomly sampled Google Street View (GSV) images are the most effective dataset for the CNN model, achieving an f1-score of 84.33%. Among the network architectures tested, MobileNet demonstrated superior performance on the majority of evaluated datasets. As the sample size increases by about 350% in the dataset, there is a positive correlation with up to 2.3% f1-score improvement. Using the best-performing CNN model, two building vulnerability models were employed to assess the spatial distribution of building damage in the urban area of Bandung, considering a hypothetical scenario of an M7 earthquake. Incorporating local construction data, one of the generated maps estimated that approximately 55% of buildings in Bandung would experience moderate to severe structural damage. This study showcases the potential of CNN models in automating regional seismic assessments and providing valuable insights for comprehensive seismic mitigation strategies.

Adaptive Vulnerability Matching Assessment: A Holistic Approach for Cyber security Resilience

Abstract: In the rapidly evolving landscape of cyber security threats, organizations face the critical challenge of identifying and mitigating vulnerabilities to protect their digital assets. Organizations are left vulnerable to possible security incidents and breaches because traditional vulnerability assessment approaches frequently cannot keep up with the ever-changing nature of cyber threats. To address this challenge, we present Vulnerability Matching assessment, a comprehensive framework designed to enhance cyber security resilience through adaptive vulnerability management. The aim is to provide an efficient and userfriendly solution for identifying and addressing security vulnerabilities, which will ultimately enhance the overall security posture of the scanned software or systems. The program will provide users with comprehensive reports so they can fix the vulnerabilities found.

Federated Learning-based Routing Vulnerability Analysis and Attack Detection for Healthcare 4.0

Federated Learning-based Routing Vulnerability Analysis and Attack Detection for Healthcare 4.0

Assessment of Flood Vulnerability and Coping Strategies of Communities Living along River Tana in Madogo Ward, Kenya

Purpose: Flood is a natural disaster that occurs due to the sudden onset of rainfall that causes runoff waters from high to low altitude area. Community living along the River Tana in Madogo ward, Tana River County are affected by the floods when it occurs. It was therefore important to assess factors contributing to their flood vulnerability and assess their flood coping and adaptation strategy for current and future planning. This study assessed the factors contributing to flood vulnerability, adaptation and coping strategies along River Tana in Madogo Ward, Tana River County, Kenya. The research objectives were to assess the trends of flood occurrence in Madogo Ward between 2000 and 2020 as well as the coping and adaptation strategies of communities to floods in Madogo Ward.
 Materials and Methods: A descriptive research design approach was used. Data collection approaches involved the use of questionnaires to identify coping strategies by communities. Key informant interviews were also conducted with government officers within the study area to provide information on factors contributing to flood vulnerability, flood trends, occurrence adaptation and coping strategies. Secondary data was acquired through journals, books, and maps. The Statistical Package for Social Science was used to analyze the quantitative data. The analyzed data was presented through maps, tables, figures and graphs.
 Findings: The results indicated that the floods occur after every two years in the study area with different magnitudes and durations. The main coping strategies employed by the community living along River Tana in Madogo Ward was relocation to the higher grounds. It was also established that the community in the area had developed adaptive strategies to flood by putting barriers round their houses. Further findings indicated that the major flood vulnerability factor was topography of the area.
 Implications to Theory, Practice and Policy: Based on the findings, it is being recommended that community leaders and county government of Tana River should not allocate plots in the flood zone area. Hence, there is a need for flood zone mapping for resident to know whether they are living within flood zone or not. Additionally, the people’s economic power should be enhanced through entrepreneurial training and giving them first priority in job opportunities. There is also a need to improve the quality of the infrastructures in the area to enhance their resilience to the negative impact of floods.

An integrated structural model for supply chain vulnerability influencing factors in manufacturing enterprises

Purpose Supply chain vulnerability (SCV) analysis is vital for manufacturers globally because it creates a pathway for building resilient supply chains in uncertain environments. This study aims to identify drivers of SCV in the Indian manufacturing sector. Design/methodology/approach Sixteen drivers were identified from the literature review and followed by expert interviews. Interpretive structural modeling was used to determine the hierarchical structural relationship among identified SCV factors. Findings It was found that risk is not a board room agenda. Misaligned performance measures with incentives and lack of risk dashboard are the causal factors of SCV. Supply chain security, centralized production and distribution and lack of trust in the supply chain were driven factors. Originality/value This provides new insights to assess and prioritize initiatives for supply chain sustainability in terms of continuing business operations. The structural model provides a systemic view of SCV and helps reduce vulnerability.

ВЫЯВЛЕНИЕ ПРОБЛЕМ ИНФОРМАЦИОННОЙ БЕЗОПАСНОСТИ МЕТОДОМ СИСТЕМАТИЧЕСКОГО ОБЗОРА ЛИТЕРАТУРЫ

The field of information security covers a wide range of technical, organizational and social aspects, requiring information security specialists to take a unique and comprehensive approach to the development, support, operation, evaluation and improvement of information security management systems. An important element of successful information protection is the accurate identification and assessment of risks and vulnerabilities that may become a source of threats. In existing publications, as a rule, it is assumed that specialists have the necessary experience and knowledge to conduct risk analysis. However, in the dynamic world of information technology and threats, an information security specialist faces a huge amount of information and potential risks that are constantly evolving. Because of this, it is an impossible task to keep in mind all kinds of threats to information security. 
 The purpose is to identify actual problems of information security, potentially acting as sources of information security risk, based on the method of systematic review of the literature. Results: 73 actual problems of information security have been identified, which an information security specialist should take into account in his activities. Understanding these issues makes it possible to develop more effective protection strategies, as well as to make informed and informed decisions when developing and applying security measures.

ATTACK VULNERABILITY OF FRACTAL SCALE-FREE NETWORK

An in-depth analysis of the attack vulnerability of fractal scale-free networks is of great significance for designing robust networks. Previous studies have mainly focused on the impact of fractal property on attack vulnerability of scale-free networks under static node attacks, while we extend the study to the cases of various types of targeted attacks, and explore the relationship between the attack vulnerability of fractal scale-free networks and the fractal dimension. A hierarchical multiplicative growth model is first proposed to generate scale-free networks with the same structural properties except for the fractal dimension. Furthermore, the fractal dimension of the network is calculated using two methods, namely, the box-covering method and the cluster-growing method, to exclude the possibility of differences in conclusions caused by the methods of calculating the fractal dimension for the subsequent relationship analysis. Finally, four attack strategies are used to attack the network, and the network performance is quantitatively measured by three structural indicators. Results on model networks show that compared to non-fractal modular networks, fractal scale-free networks are more robust to both static and dynamic targeted attacks on nodes and links, and the robustness of the network increases as the fractal dimension decreases. However, there is a cost in that as the fractal dimension decreases, the network becomes less efficient and more vulnerable to random failures on links. These findings contribute to a deeper understanding of the impact of fractal property on scale-free network performance and may be useful for designing resilient infrastructures.

Carving Drought Impact Over Purulia District, West Bengal, India

Purulia was the westernmost district of West Bengal (from 1956) and is drought-prone due to deficient rainfall, its undulating topography with rugged hilly terrains and its positioning near the Tropic of Cancer, the spatial evaluation of vulnerable and risk-prone places.
 The various impacts of drought, such as meteorological, hydrological, and agricultural, are assessed by considering the meteorological parameters, vulnerability, and risk levels. The fundamental factors impacting susceptibility and risk are recognised, and the drought years are analysed. The methodologies applied GIS technology, EREDAS, and secondary data were collected to analyse the type of drought. The intensities and types of droughts: a spatial analysis and relative vulnerability assessment of the Kashipur/ Purulia block by Remote Sensing and GIS. Analysis of pre- and post-monsoon meteorological and Agricultural drought.
 Agriculture is a climate-sensitive activity. The mechanism is to know the farmers, what crops to grow, when suitable, the climatic parameters, temperature, rainfall concentration, and seasonal hazards. A well-planned agriculture practice has been proposed, and an adequately calculated water budget, catchment treatment plan, and implementation of a perfect crop plan, seeds, manures, and pesticides are the weapons of the drought-hit Purulia/Kashipur farmers.

Quantum-inspired analysis of neural network vulnerabilities: The role of conjugate variables in system attacks

Abstract Neural networks demonstrate vulnerability to small, non-random perturbations, emerging as adversarial attacks. Such attacks, born from the gradient of the loss function relative to the input, are discerned as input conjugates, revealing a systemic fragility within the network structure. Intriguingly, a mathematical congruence manifests between this mechanism and the quantum physics’ uncertainty principle, casting light on a hitherto unanticipated interdisciplinarity. This inherent susceptibility within neural network systems is generally intrinsic, highlighting not only the innate vulnerability of these networks but also suggesting potential advancements in the interdisciplinary area for understanding these black-box networks.

Simplified Vulnerability Assessment of Historical Churches in Banat Seismic Region, Romania

ABSTRACT Romania, a mid-eastern European country, has a moderate seismicity and a large stock of historical buildings and churches. One of the most important seismic areas of the country is the Banat area, which ranks as the second most seismic area in Romania, with shallow earthquakes of crustal type. Many Orthodox and Catholic churches can be found in the area, the majority of them having a central nave. The churches are built in masonry, with vaults and wooden frameworks, and they present valuable architectural-artistic details, including paintings made by recognized painters. Various forms of structural damage appeared to the historical churches after past earthquakes, depending on the architectural configuration. This paper illustrates a study made on six historic churches in the Banat region, to investigate seismic vulnerability with simplified methods. The study highlights the most vulnerable points of the historic religious structures and the importance of investigating in a quick and simplified way the seismic behavior of such important buildings for the local community. Moreover, the main novelty of the paper is the highlighting of the importance of the sustainability aspect in the process of heritage preservation, as simplified assessment procedures are essential for more resilient risk reduction policies.

Alcance y desafíos de las relaciones mente-cerebro en el contexto del diálogo entre la neurociencia y la filosofía

The so-called «mind-brain relationships» are shown to be a privileged place for understanding the human being in a unitary way in its biological and psychic aspects. This reveals the need for an interdisciplinary approach to understand the human being in an integral way. This approach can be carried out, at least, in two directions, taking as a model the dialogue between neuroscience and philosophy. The first one goes from neuroscience to philosophy and covers, above all, the subject of knowledge, mainly in the so-called inner senses. The second extends from philosophy to neuroscience by exploring topics such as attention, memory and habits. From this vision, an understanding of mind-brain relationships arises in which the interdisciplinary approach is extremely important. From it, we propose a possible application of these relationships to the ethical sphere, inspired by the philosopher Alasdair MacIntyre in his analysis of human vulnerability in a context of social co-dependence.

A Literature Survey on System Security and Network Vulnerability Assessment

This abstract outlines a detailed study on improving network security through vulnerability assessment and penetration testing, using tools like Nessus, Nmap, Metasploit, on the Kali Linux OS. The methodology involves identifying vulnerabilities, conducting simulated attacks, and developing a bash script to address false positives from Nessus scans. The research aims to enhance network security, provide practical recommendations, and contribute to cybersecurity practices, with a focus on both internal and external network security. Keywords: Vulnerability Assessment, Pentest, Nessus, Metasploit, Kali Linux

Adapting cities to the surge: A comprehensive review of climate-induced urban flooding

Climate change is a serious global issue causing more extreme weather patterns, resulting in more frequent and severe events like urban flooding. This review explores the connection between climate change and urban flooding, offering statistical, scientific, and advanced perspectives. Analyses of precipitation patterns show clear changes, establishing a strong link between climate change and the heightened intensity of global rainfall events. Hydrological modeling and case studies provide compelling scientific evidence attributing urban flooding to climate-induced changes. Urban infrastructure, including transportation networks and critical facilities, is increasingly vulnerable, worsening the impact on people's lives and businesses. Examining adaptation strategies, the review highlights the need for resilient urban planning and the integration of green infrastructure. Additionally, it delves into the role of advanced technologies, such as artificial intelligence, remote sensing, and predictive modeling, in improving flood prediction, monitoring, and management. The socio-economic implications of urban flooding are discussed, emphasizing unequal vulnerability and the importance of inclusive policies. In conclusion, the review stresses the urgency of addressing climate-induced urban flooding through a holistic analysis of statistical trends, scientific evidence, infrastructure vulnerabilities, and adaptive measures. The integration of advanced technologies and a comprehensive understanding of socio-economic implications are essential for developing effective, inclusive strategies. This review serves as a valuable resource, offering insights for policymakers, researchers, and practitioners striving for climate-resilient urban futures amid escalating climate change impacts.

Development and Standardization of a Climate Vulnerability Index to Measure the Vulnerability Indices of Paddy Growers

India is prominently recognized as the foremost producer of paddy, cultivating this crop over 47.83 million hectares and generating 135.75 million tonnes of paddy, thus playing a substantial role in the worldwide paddy output. However, there is an anticipated decline in paddy production yields due to the projected effects of climate change, estimated to range from 10% to 30% by 2030. The assessment of vulnerability will give a comprehensive picture of current and future climate change risks with more stress factors to be anticipated. It will help identify opportunities arising from climate change, and provide information on how to assess adaptive capacity and cope with uncertainty. Adaptation cannot be planned based on the climate projections; information on risk and vulnerabilities is also needed to determine how the climate interacts with socio-economic issues. Against this backdrop, the proposed research seeks to fill this crucial knowledge gap by developing and constructing vulnerability indices tailored specifically for paddy growers in India. Based on review of literature and discussion with experts, three dimensions along with indicators and sub-indicators by adopting the indicator approach method under the vulnerability indices of paddy growers due to climate change were identified. The relevancy rating score was obtained from 50 experts in the concerned area. Based on the relevancy score, 17 indicators and 65 sub-indicators of 0.80 and above were considered for inclusion in the vulnerability index. To compute the index values for each of the identified dimensions, their relative importance in the vulnerability was worked out by assignment of weights to indicators and sub-indicators under each dimension through Principal component analysis (PCA) and the findings revealed that sensitivity was observed to be in the top position (8.36), followed by exposure (8.28) and adaptive capacity (5.61) in assessing the climate vulnerability of paddy growers.

Rapidly Developing a Community and Evidence Based Heat Action Plan

Abstract Extreme heat contributes to 8,000 to 12,000 excess U.S. deaths per year. Partly due to increasing summer temperatures and a renewed focus on environmental justice, local governments started new initiatives to manage and adapt to extreme heat. For example, Miami-Dade County, Florida, U.S., appointed Jane Gilbert as the world’s first Chief Heat Officer. This manuscript summarizes Miami- Dade County’s preliminary efforts to build local evidence, engage the community, and rapidly respond to extreme heat. The manuscript’s goal is to expedite the translation of existing tools into mainstream extreme heat, health, and equity planning. The study generated local evidence to identify the places and periods of time with elevated heat related illness using a statistical vulnerability and time series analysis, respectively. The places with the highest severe heat-related illness rates had hotter land surface temperatures and/or higher proportions of people who were outdoor workers, indigenous, living in poverty or mobile homes, and households with children. “Everyday” summer conditions instead of rare heatwaves increase the risk of a heat related death. The Chief Heat Officer convened workshops that engaged 298 unique community members on six cross-sectoral heat topics. Key recommendations included: increasing multi-sectoral heat monitoring and risk communication, building more affordable housing, preserving and expanding greenspace, and creating heat resilience hubs. The activities culminated in a Heat Action Plan, which was completed in less than two years from the receipt of project funding.

Vulnerability Detection in Intelligent Environments Authenticated by the OAuth 2.0 Protocol over HTTP/HTTPS

OAuth 2.0 provides an open secure protocol for authorizing users across the web. However, many modalities of this standard allow these protections to be implemented optionally. Thus, its use does not guarantee security by itself and some of the deployment options in the OAuth 2.0 specification can lead to incorrect settings. FIWARE is an open platform for developing Internet applications of the future. It is the result of the international entity Future Internet Public-Private Partnership. [1,2] FIWARE was designed to provide a broad set of API to stimulate the development of new businesses in the context of the European Union. This platform can be understood as a modular structure to reach a broad spectrum of applications such as IoT, big data, smart device management, security, open data, and virtualization, among others. Regarding security, the exchange of messages between its components is done through the OAuth 2.0 protocol. The objective of the present work is to create a system that allows the detection and analysis of vulnerabilities of OAuth 2.0, executed on HTTP/HTTPS in an on-premise development environment focused on the management of IoT devices and to help developers to implement them ensuring security for these environments. Through the system proposed by this paper, it was possible to find vulnerabilities in FIWARE components in HTTP/HTTPS environments. With this evidence, mitigations were proposed based on the mandatory recommendations by the IETF.

Assessment of Eco-Environmental Vulnerability Using Remote Sensing and GIS Tools in Maharashtra Region, India

Maharashtra region is prone to various disasters such as drought, floods, cyclones and earthquake and has been exposed to extreme weather events like dry spells. Communities within these dry lands are poor and face extreme conditions of water stress. This study has been carried out to analyze and quantify climatic and anthropogenic effect on eco-environmental vulnerability dynamic change. To achieve that a numerical model is set up, consisting of eight factors that are elevation, land use, drought, slope, NDVI, soil-type, soil erosion (water), and population density index & has been evaluated using the method of spatial principle component analysis (SPCA) on Remote Sensing and GIS platform. The integrated eco-environmental vulnerability index (EVI) of study area is estimated to analyse spatial-temporal dynamic vulnerability changes in the 11 years gap from 2000 and 2011. The results show that the study area has become eco-environmental vulnerable slightly (about 80% of the region) with an increased eco-environmental vulnerability integrated index (EVSI) value by more than 50% (i.e., about 74%) and the driving force of dynamic change is mainly caused by socio-economic activities. In addition the estimation has been regionalized into thirty-four districts to serve as a base for decision-making for eco-environmental recovering and rebuilding. It is found that the most vulnerable district in 2011 is Ratnagiri and the least one is Sangli. There are nine districts which shows more than 100% increase in EVSI value, with the highest increase in Hingoli(100.65%), indicating that the districts have become most environmental vulnerable in the study-period. The research concludes that the method, supported by G.I.S using SPCA can’t only represent distinctly the input spatial distribution of plain-mountain-belt feature, but also respect the whole river-valley as a single unit.

Detour-RS: Reroute Attack Vulnerability Assessment with Awareness of the Layout and Resource

Recent decades have witnessed a remarkable pace of innovation and performance improvements in integrated circuits (ICs), which have become indispensable in an array of critical applications ranging from military infrastructure to personal healthcare. Meanwhile, recent developments have brought physical security to the forefront of concern, particularly considering the valuable assets handled and stored within ICs. Among the various invasive attack vectors, micro-probing attacks have risen as a particularly menacing threat. These attacks leverage advanced focused ion beam (FIB) systems to enable post-silicon secret eavesdropping and circuit modifications with minimal traceability. As an evolved variant of micro-probing attacks, reroute attacks possess the ability to actively disable built-in shielding measures, granting access to the security-sensitive signals concealed beneath. To address and counter these emerging challenges, we introduce a layout-level framework known as Detour-RS. This framework is designed to automatically assess potential vulnerabilities, offering a systematic approach to identifying and mitigating exploitable weaknesses. Specifically, we employed a combination of linear and nonlinear programming-based approaches to identify the layout-aware attack costs in reroute attempts given specific target assets. The experimental results indicate that shielded designs outperform non-shielded structures against reroute attacks. Furthermore, among the two-layer shield configurations, the orthogonal layout exhibits better performance compared to the parallel arrangement. Furthermore, we explore both independent and dependent scenarios, where the latter accounts for potential interference among circuit edit locations. Notably, our results demonstrate a substantial near 50% increase in attack cost when employing the more realistic dependent estimation approach. In addition, we also propose time and gas consumption metrics to evaluate the resource consumption of the attackers, which provides a perspective for evaluating reroute attack efforts. We have collected the results for different categories of target assets and also the average resource consumption for each via, required during FIB reroute attack.

Systematic literature review: Digital twins' role in enhancing security for Industry 4.0 applications

AbstractConnectivity and data exchange are key features of Industry 4.0. In this paradigm, (Industrial) Internet of Things ((I)IoT) devices are a vital component facilitating the collection and transmission of environmental data from the physical system to the central station for processing and analysis (digital twin [DT]). However, although (I)IoT devices play a critical role in this process, they are not inherently equipped to run strong encryption mechanisms to secure the data they transmit over wired or wireless channels. This research aims to explore the potential of DTs in securing Industry 4.0 applications and the security mechanism employed to ensure confidentiality, integrity, and authentication of data communicated between (I)IoT and DT through a systematic literature review (SLR). This SLR, based on the analysis of 67 papers published between 2018 and 2023, underscores the evolving significance of DT technology, particularly within the ambit of Industry 4.0. The findings illuminate the pervasive influence of DT technology across multiple industrial sectors. The result SLR revealed that DT is growing and being widely adopted as a security tool particularly in Industry 4.0 using enabling technology like machine learning, data analytics, blockchain, and 5G networks to provide security solutions such as intrusion detection, vulnerability assessment, cyber range, and threat intelligence.