Current Vulnerability Research Articles

Migration tracking reveals geographic variation in the vulnerability of a Nearctic-Neotropical migrant bird

We compared the vulnerability of a Nearctic-Neotropical migrant (Swainson’s Thrush, Catharus ustulatus) for three geographically-defined breeding populations in California by linking breeding and wintering regions, estimating migration distances, and quantifying relative forest loss. Using data from light-level geolocator and GPS tags, we found that breeding birds from the relatively robust coastal population in the San Francisco Bay area wintered predominantly in western Mexico (n = 18), whereas the far rarer breeding birds from two inland populations that occur near one another in the Sierra Nevada and southern Cascades mountain ranges migrated to farther wintering destinations, with birds from the Lassen region (n = 5) predominantly going to Central America and birds from the Tahoe region (n = 7) predominantly to South America. Landscape-level relative forest loss was greater in the breeding and wintering regions of the two Cascade-Sierra populations than those of coastal birds. Longer migration distances and greater exposure to recent forest loss suggest greater current vulnerability of Cascade-Sierra birds. Our results demonstrate that for some species, quantifying migration distances and destinations across relatively small distances among breeding populations (in this case, 140–250 km apart) can identify dramatically different vulnerabilities that need to be considered in conservation planning.

Freshwater fish diversity hotspots for conservation priorities in the Amazon Basin.

Conserving freshwater habitats and their biodiversity in the Amazon Basin is a growing challenge in the face of rapid anthropogenic changes. We used the most comprehensive fish-occurrence database available (2355 valid species; 21,248 sampling points) and 3 ecological criteria (irreplaceability, representativeness, and vulnerability) to identify biodiversity hotspots based on 6 conservation templates (3 proactive, 1 reactive, 1 representative, and 1 balanced) to provide a set of alternative planning solutions for freshwater fish protection in the Amazon Basin. We identified empirically for each template the 17% of sub-basins that should be conserved and performed a prioritization analysis by identifying current and future (2050) threats (i.e., degree of deforestation and habitat fragmentation by dams). Two of our 3 proactive templates had around 65% of their surface covered by protected areas; high levels of irreplaceability (60% of endemics) and representativeness (71% of the Amazonian fish fauna); and low current and future vulnerability. These 2 templates, then, seemed more robust for conservation prioritization. The future of the selected sub-basins in these 2 proactive templates is not immediately threatened by human activities, and these sub-basins host the largest part of Amazonian biodiversity. They could easily be conserved if no additional threats occur between now and 2050.

Insider and outsider support for unions across advanced industrial democracies: Paradoxes of solidarity

Why do workers support trade unions? For insider–outsider analysts, unions display limited concern with representing interests beyond the full-time labour force. However, recent research on union revitalization and inclusionary practices stresses new initiatives towards labour market outsiders. We use multilevel regression models, employing data from the 2005 and 2015 International Social Survey Programme, in order to study how workers perceive the role of unions. We develop a four-quadrant categorization of insiders and outsiders that captures both current labour market status and vulnerability. We find that outsiders, and more specifically all categories of non-insiders, are more likely to agree with the need for strong unions than insiders. These results hold both before and after the Great Recession.

Port stakeholder perceptions of Sandy impacts: a case study of Red Hook, New York

ABSTRACT Understanding the impacts of coastal storm hazards on all maritime port system stakeholders (e.g. operators, tenants, clients, workers, communities, governments) is essential to comprehensive climate change resilience planning. While direct damages and indirect impacts are quantifiable through economic data and modeling, qualitative data on the intangible consequences of storms are necessary to explicate interdependencies between stakeholders as well as conditions that substantially affect response and recovery capacities. This case study explores Hurricane Sandy storm impacts using evidence solicited from stakeholder representatives and extracted from contemporaneous and technical accounts of storm impacts on the port system at Red Hook Container Terminal, Brooklyn, New York, USA. Results highlight the wide range of direct damages, indirect costs, and intangible consequences impacting stakeholders across institutional boundaries and requiring coordination for recovery, providing insight into stakeholder relationships and dependencies in the post-disaster response and recovery process that are often not fully accounted for in current vulnerability assessment and response planning methodologies.

Risk, poverty or politics? The determinants of subnational public spending allocation for adaptive disaster risk reduction in Bangladesh

Abstract We examine the directly observable determinants of sub-national (central to local) public spending allocations for disaster risk reduction and climate adaptation in Bangladesh, a country with a very high exposure to weather risk. We use a comprehensive dataset for the 483 sub-districts (Upazilas) in Bangladesh, tracking disaster risk reduction and adaptation funding provided to each sub-district by the central government during fiscal years’ 2010–11 to 2013–14, disaggregated by the various types of social protection programs. We assess to what extent the primary determinants of such funding flows—such as current hazard risk, socio-economic vulnerability, and political economy considerations—contribute to these funding allocation decisions. We find that flood hazard risk and socio-economic vulnerability are both positively correlated with the sub-district fiscal allocations. We find that political factors do not seem to significantly correlate with these allocations and neither does proximity to the centres of Dhaka and Chittagong. Public spending for adaptive disaster risk reduction, as investigated here, can be a useful complementary intervention tool to other DRR programs, such as insurance or broader social transfers, provided that it is allocated rationally. Broadly, this appears to be the case in Bangladesh. We leave the measuring of the relative efficacy and efficiency of each financing tool for future work.

A vulnerability analysis and prediction framework

As the world approaches a state of greater dependence on technology, many products face increasing threats from malicious attackers who are attempting to take advantage of vulnerabilities in software design. Most of the known vulnerability information is already aggregated, stored in text format, and readily accessible to the public, making such an aggregated database a prime corpus for analysis using data mining methods. Multiple research efforts have been launched in which individual aspects of such cyber-security corpora were analyzed to create taxonomies, assess vulnerability impact, and improve vulnerability detection. However, minimal effort has been committed to analyze cyber-security corpora to explore correlations between vulnerabilities, to study the evolution of a vulnerability from its genesis, and to predict vulnerabilities using multi-faceted algorithms. In this paper, we propose an integrated data mining framework to automatically describe how vulnerabilities develop over time and detect the evolution of a specific vulnerability. Additionally, our framework has a predictive functionality that can be used to predict specific vulnerabilities or to estimate future appearance probabilities of vulnerability groups. In our framework, we use (1) a Topically Supervised Evolution Model (TSEM) that can discover temporal themes from a text corpus, (2) a diffusion-based storytelling technique that sifts through past vulnerability reports to describe how a current vulnerability threat evolved, and (3) several prediction models that use features from a cyber-security corpus to predict vulnerabilities. A series of experiments demonstrate that the proposed framework can not only discover evolutionary patterns in today's most pressing vulnerabilities with a high degree of precision, but it can also predict vulnerabilities with impressive accuracy. As case studies, we also explore the development of vulnerabilities in certain products, providing a unique insight into the correspondence between seemingly unrelated vulnerabilities and the impact of that correspondence on overall software security.

Les transformations morphologiques du tissu bâti de Beyrouth depuis 1950

Cet article présente une méthode d’analyse du bâti de Beyrouth-municipe permettant de resituer les transformations du bâti dans une trajectoire spatio-temporelle débutant au milieu des années 1950, et de distinguer ainsi, les évolutions récentes de celles opérant sur le temps long. Pour parvenir à cet objectif, une démarche inédite de création de l’information spatio-morphologique a été réalisée à une échelle fine. Les analyses dégagent les tendances générales opérées sur les cinquante dernières années, ainsi que les spécificités géographiques qui résultent à la fois de la transformation incessante de la ville et de la reconstruction de l’après-guerre civile. Elles soulignent en outre, les conséquences de l’évolution morphologique du bâti sur la vulnérabilité actuelle face aux séismes considérés comme un risque majeur pour la ville de Beyrouth.

Real-Time Multistep Attack Prediction Based on Hidden Markov Models

A novel method based on the Hidden Markov Model is proposed to predict multistep attacks using IDS alerts. We consider the hidden states as similar phases of a particular type of attack. As a result, it can be easily adapted to multistep attacks and foresee the next steps of an attacker. To achieve this goal, a preliminary off-line training phase based on observations will be required. These observations are obtained by matching the IDS alert information with a database previously built for this purpose using a clusterization method from the CVE global database to avoid overfitting. The training model is performed using both unsupervised and supervised algorithms. Once the training is completed and probability matrices are computed, the prediction module compute the best state sequence based on the state probability for each step of the multistep attack in progress using the Viterbi and forward-backward algorithms. The training model includes the mean number of alerts and the number of alerts in progress to assist in obtaining the final attack probability. The model is analyzed for DDoS phases because it is a great problem in all Internet services. The proposed method is validated into a virtual DDoS scenario using current vulnerabilities. The results proving the system's ability to perform real-time prediction.

Climate change induced migration: A study on informal settlement in Dhaka city

The purpose of this paper to know decision making plan of urban migrant people of urban slam in Dhaka city in the context of climate change. Besides this study also make out the reason of migration for the settlement of urban slam and the current socio economic situation and vulnerability of those who have moved to urban as slam dwellers. The study conducted at two slum of Dhaka with purposive sample survey, KII and in depth qualitative interview of selected climate migrant slum dwellers. The study found that migrants residing in urban side-line of Dhaka city slum have been using migration as livelihood or survival strategy for quite some times. Mainstream migration literature of Bangladesh mostly highlighted economic, social and demographic challenges as drivers of rural‚ urban migration. This study found that many economic, social and demographic challenges that led to migration decision of the slum dwellers are deeply bounded with the environmental or climatic stresses of the areas of their origin. Migrants of Dhaka slum mostly experienced environmental stresses, i.e. riverbank erosion, cyclone, flood, water logging drought and salinity. In other words, these groups of people have taken help of different types of migration (short-term, cyclical, seasonal or permanent) to adapt to the changes that took place in their lives due to social and economic reasons influenced by climatic stresses. After migration city slum’s vulnerability represents necessary reformulation of the existing policies on migration in the context of climate change. This study effort to identify the major climatic stress and shocks in the decision to migrate. It also clarify livelihood pursued by migrants and other house members. This study is on adaptation strategies of urban migrants in the context of climate change.

The Determinants of Subnational Public Spending Allocation for Disaster Risk Reduction in Bangladesh

We examine the directly observable determinants of sub-national (central to local) public spending allocations for disaster risk reduction and climate adaptation in Bangladesh, a country with a very high exposure to weather risk. We use a comprehensive dataset for the 483 sub-districts (Upazilas) in Bangladesh, tracking disaster risk reduction and adaptation funding provided to each sub-district by the central government during fiscal years’ 2010-11 to 2013-14, disaggregated by the various types of social protection programs. We assess to what extent the primary determinants of such funding flows—such as current hazard risk, socio-economic vulnerability, and political economy considerations—contribute to these funding allocation decisions. We find that flood hazard risk and socio-economic vulnerability are both positively correlated with the sub-district fiscal allocations. We find that political factors do not seem to significantly correlate with these allocations and neither does proximity to the centres of Dhaka and Chittagong. Public spending for adaptive disaster risk reduction, as investigated here, can be a useful complementary intervention tool to other DRR programs, such as insurance or broader social transfers, provided that it is allocated rationally. Broadly, this appears to be the case in Bangladesh. We leave the measuring of the relative efficacy and efficiency of each financing tool for future work.

Climate Variability, Change and the Impacts on Livelihood Vulnerability of Farming Households in Koronadal, South Cotabato, Philippines

This study examined the changes and variability in temperature and rainfall patterns in the past 31 years (1981-2012) and assessed their impacts on livelihood vulnerability of farming households in the City of Koronadal, South Cotabato, a less studied area in Mindanao located in Southern Philippines. Using the Intergovernmental Panel on Climate Change (IPCC) framework, household vulnerability was assessed using survey data from 265 respondents, complemented with focus group discussion, and field observations from 2013 to 2015. Results showed significant changes in monthly mean minimum (increased by 0.74 C, p <0.01) and mean maximum (decreased by 0.65C, p <0.01) temperature. Rainfall patterns showed a decreasing trend and revealed significant changes in June (p<0.01), August, and December (p<0.05), signifying that climate change and variability took place as manifested by floods, landslides, and drought experienced by farming households. The study confirmed that majority of the farming households had “moderate to high vulnerability” to climate variability and change. As climate change brings new forms of risks, appropriate adaptation strategies are needed to address both current and future vulnerability and require robust vulnerability assessment founded on recent scientific advancement and innovative strategies congruent to this study.

How do community-level climate change vulnerability assessments treat future vulnerability and integrate diverse datasets? A review of the literature

Community-level vulnerability assessments (VAs) are important for understanding how populations experience vulnerabilities to climate change in different ways given local socioeconomic and environmental factors. Despite recent expansion in the literature that evaluates vulnerability at the local level, approaches to understanding future scenarios and to integrating climatic and nonclimatic factors are inconsistent and often lack clear methodological information. This study utilized systematic review methods to characterize and compare future scenarios and the integration of climatic and nonclimatic stimuli in community-focused VAs published over the last five years. Five common methods for assessing future dimensions of vulnerability were characterized. Key challenges regarding sources and scales of information were highlighted alongside methods to integrate data spanning climatic and nonclimatic information at scales ranging from local to global. The majority of VAs considered current and past vulnerability; few VAs incorporated future scenarios and these studies focused on future climatic conditions while largely overlooking changes in nonclimatic drivers of vulnerability. Approaches to evaluate future dimensions of vulnerability included climate model projections, socioeconomic model projections, temporal analogue approaches, longitudinal approaches, and local perceptions. These methods often failed to capture the dynamic interactions between variables through time, as future impacts are unlikely to follow previous patterns of change. To combine datasets of different scales, VAs created vulnerability indices, overlaid spatial datasets, or used expert judgement. These approaches tended to aggregate local characteristics to the regional level at the expense of community specificity. There is a need for methodological advances to assess future scenarios and to combine datasets in the field of community-level climate change VAs to make these studies more responsive to local realities and relevant to the development of climate change adaptation strategies.

EXPEDITIOUS METHODS OF URBAN SURVEY FOR SEISMIC VULNERABILITY ASSESSMENTS

Abstract. The aim of the proposal is to illustrate how expeditious procedures of urban survey carried out through photomodeling can be the most suitable representation tool in combination with an expeditious procedure for assessing the seismic vulnerability of the historic building heritage in Italian city centres. For some years, in fact, the research group is developing a protocol for the rapid assessment of the seismic vulnerability of masonry aggregate buildings in Italian historic centres.The protocol is based on the determination of synthetic indicators providing a preventive quantification of the possible earthquake damage. This evaluation procedure is oriented to prevent and reduce the current vulnerability, aiming at the conservation and preservation of the historic building heritage. The synthetic indicators are defined by identifying expeditious evaluation procedures based on the typical evolutionary processes suffered by each aggregate in its planimetric and height development, on the construction techniques and on the design concepts used in the local area; these aspects are directly correlated to failure modes.The application of the entire process (starting from the rapid survey phases up to the final restitution of the seismic vulnerability assessment results) is illustrated for the historic centre of Imola. The ancient nucleus of this city constitutes an excellent example, as it is clearly representative of the Emilian historical architecture both for the processes of formation and transformation of the inhabited area, both for what concerns the constructive characterization deriving from the local building traditions.

Flood Vulnerability Assessment through Different Methodological Approaches in the Context of North-West Khyber Pakhtunkhwa, Pakistan

There are several approaches to assess flood vulnerability as a proactive measure to reduce the risk of flooding. The indicator-based approach is primarily practiced from a policy point of view through the use of composite indicators. Composite indicators can be built from very easy to very complex and sophisticated methods. However, there are two complications that arise with this issue. On the one hand, the flood vulnerability index should be fairly simple, taking into account the interdisciplinary nature of various stakeholders involved in flood risk management. While on the other hand, addressing the issue of subjectivity or prejudice should be scientifically defensible. As there is no a single universally “best” methodological approach for the construction of composite indicator due to its data-specific nature for each individual study. The aim of this study is therefore to construct such an index of flood vulnerability that is not only intuitive to a variety of stakeholders, but also scientifically justified in the context of Khyber Pakhtunkhwa, Pakistan. Therefore, the current study demonstrated a detailed procedure to construct the flood vulnerability indices through different methodological approaches of data rescaling, weighting, and aggregation schemes, along with a fairly simple approach for robustness. For this purpose, data was collected through different (official) portals for the nine highly flood-prone districts of the Khyber Pakhtunkhwa. It was found that the weighting schemes had a greater influence on the flood vulnerability ranking of the selected districts compared to data rescaling and aggregation schemes. The simple model, which is the frequently using approach of building composite indicators in scientific community, was found to be appropriate for the selected data. The methodology adopted in the study can provide decision-makers and relevant authorities with a practical tool to identify and prioritize certain vulnerable areas and measures to mitigate current flood vulnerabilities while preparing for future flood risk mitigation in the province through a fairly simple and methodologically defensible approach.

Climate change adaptation in coastal cities of developing countries: characterizing types of vulnerability and adaptation options

Facing the increasingly adverse impacts of climate change, many coastal cities in developing and least-developed countries have shaped their climate adaptation plan. This study aims to unpack the state-of-the-art municipal adaptation planning in developing countries. The paper seeks to understand the types of vulnerability and explore planned adaptation options through a content analysis of adaptation planning documents in 45 selected coastal cities in developing countries. The result shows the complexity of vulnerabilities that are not only climate change impacts, but more importantly, the socio-economic sensitivity, the insufficient infrastructure system, and limited adaptive capacity. Adaptation responses, correspondingly, address primarily current vulnerabilities rather than future climate change impacts. Local climate change adaptation in developing countries, therefore, cannot separate from socio-economic development and capacity enhancement. A coordination mechanism for inter-policy is necessary to manage the trade-offs between multiple priorities.

Synchronization of Critical Infrastructures Dependent Upon GNSS: Current Vulnerabilities and Protection Provided by New Signals

Many infrastructures that shape our lifestyle depend on the GPS. Even though not used for positioning, these infrastructures need GPS to derive a precise time synchronization necessary for their operations. Examples are power distribution grids, gateways for financial transactions, and telecommunication networks. However, GPS receivers, and more in general g lobal navigation satellite system (GNSS) receivers, are vulnerable to interference. This makes GNSS-dependent infrastructures prone to time synchronization errors. This paper addresses the vulnerability of GNSS receivers to the intentional injection of counterfeit signals, an operation known as “spoofing.” The analysis is backed by a campaign of tests conducted on three receivers suitable for applications that use GNSS-based synchronization. A battery of spoofing attacks, targeting the control of the output time reference of these receivers, is purposely simulated with lab instrumentation. The effects of such attacks on the receivers’ measurements are observed and quantified; they prove that the vulnerability of GNSS receivers to malevolent radio attacks is a quantifiable reality, but such attacks “leave traces” that could trigger their detection. The purpose of this paper is to increase awareness, though not alarm, about the risk represented by time spoofing on application domains used to look at GNSS as a commodity. This paper shows that reducing this risk is possible at both receiver and system level.

El potencial de la percepción social aplicada al análisis de la vulnerabilidad en planificación urbana

Today, the role of the social perception of urban space is scarce in the documents that guide the adequate integration of the urban development of cities. A better understanding of the influence of social relationships within the city allows new knowledge to be brought to the underlying mechanisms of vulnerability and social exclusion in the urban space. This work focuses on studying the relationship between the quantitative approach of current urban vulnerability reports and a qualitative approach based on social perception, developed within the framework of the Social Risk Map of Zaragoza (Spain) research project between 2014-2017. The cartographical analysis shows that the risk of social isolation is not greater unequivocally in the areas currently characterized as vulnerable and reveals the importance of this type of research for city and urban planning activities.

Open source software security vulnerability detection based on dynamic behavior features.

Open source software has been widely used in various industries due to its openness and flexibility, but it also brings potential security problems. Therefore, security analysis is required before using open source software. The current mainstream open source software vulnerability analysis technology is based on source code, and there are problems such as false positives, false negatives and restatements. In order to solve the problems, based on the further study of behavior feature extraction and vulnerability detection technology, a method of using dynamic behavior features to detect open source software vulnerabilities is proposed. Firstly, the relationship between open source software vulnerability and API call sequence is studied. Then, the behavioral risk vulnerability database of open source software is proposed as a support for vulnerability detection. In addition, the CNN-IndRNN classification model is constructed by improving the Independently Recurrent Neural Net-work (IndRNN) algorithm and applies to open source software security vulnerability detection. The experimental results verify the effectiveness of the proposed open source software security vulnerability detection method based on dynamic behavior features.

Cyberbiosecurity Implications for the Laboratory of the Future.

Technological innovation has become an integral and inescapable aspect of our daily existence as almost everything of significance in our world now has a cyber (i.e., relating to, or involving computers, computer networks, information technology, and virtual reality) component associated with it. Every facet of our lives is now touched by technology. As such, we're experiencing a digital transformation. Unfortunately, both as individuals and as a society, we're inadequately prepared to embrace the myriad of vulnerabilities presented by cybertechnologies. Unintended cyber vulnerabilities present significant risks to individuals, organizations, governments and economies. Here, we identify current cybersecurity vulnerabilities found in the life science enterprise and discuss the many ways in which these vulnerabilities present risk to laboratory workers in these facilities, the surrounding community and the environment. We also consider the cyberbiosecurity benefits associated with numerous innovations likely to be present in the laboratory of the future. The challenges associated with cyberbiosecurity vulnerabilities are not insurmountable; they simply require thoughtful consideration by equipment designers, software and control systems developers, and by end users. Organizations and the individuals that comprise them must respect, value, and protect their data. End users must train themselves to look at every piece of laboratory equipment and every process from a cyberbiosecurity perspective. With this approach, cyberbiosecurity vulnerabilities can be minimized or eliminated to the benefit of workers, life science organizations, and national security.

On the need to integrate uncertainty into U.S. water resource planning.

A changing climate is expected to introduce uncertainty into water resource management decision making. We examined the latest publicly-available, state-level guidance regarding the management of water supplies and demands concerning risks associated with drought, flooding, and climate change. We found state-level guidance supplementing the federally-backed flood mitigation program to be updated most regularly (54% in the last 5 years; 84% in the last decade). Yet, the underlying floodplain mapping data these local planning efforts rely on are acknowledged by the Federal Emergency Management Agency (FEMA) to be chronically outdated. Drought planning guidance was found to be most outdated (16% last updated in the last 5 years; 18% almost two decades ago), and across the U.S., almost universally (94%) reactive (emergency response) rather than proactive (mitigation or management). Although 79-94% of states provide some level of guidance regarding water supply and demand, the projections themselves may significantly predate the guidance. Many (70%) U.S. states still lack climate change impact guidance, particularly non-coastal states and those impacted by increased water scarcity rather than flooding. Strategies are rare (4%) for addressing the impacts of increased variability and uncertainty to meet inelastic demands with finite supplies. We conclude significant gaps exist in planning to address known or projected risks of climate-related impacts. Specific recommendations, including the implementation of a nationwide water census, are provided to improve both the data and knowledge base of water management and reduce current vulnerabilities.