Abstract: The automatic detection of software vulnerabilities is an important research problem. However, existing solutions to this problem rely on human experts to define features and often miss many vulnerabilities (i.e., incurring high false negative rate). In this paper, we initiate the study of using deep learning-based vulnerability detection to relieve human experts from the tedious and subjective task of manually defining features. Since deep learning is motivated to deal with problems that are very different from the problem of vulnerability detection, we need some guiding principles for applying deep learning to vulnerability detection. In particular, we need to find representations of software programs that are suitable for deep learning. For this purpose, we propose using code gadgets to represent programs and then transform them into vectors, where a code gadget is a number of (not necessarily consecutive) lines of code that are semantically related to each other. This leads to the design and implementation of a deep learning-based vulnerability detection system, called Vulnerability Deep Pecker (VulDeePecker). In order to evaluate VulDeePecker, we present the first vulnerability dataset for deep learning approaches. Experimental results show that VulDeePecker can achieve much fewer false negatives (with reasonable false positives) than other approaches. We further apply VulDeePecker to 3 software products (namely Xen, Seamonkey, and Libav) and detect 4 vulnerabilities, which are not reported in the National Vulnerability Database but were "silently" patched by the vendors when releasing later versions of these products; in contrast, these vulnerabilities are almost entirely missed by the other vulnerability detection systems we experimented with.

Abstract: The automatic detection of software vulnerabilities is an important research problem. However, existing solutions to this problem rely on human experts to define features and often miss many vulnerabilities (i.e., incurring high false negative rate). In this paper, we initiate the study of using deep learning-based vulnerability detection to relieve human experts from the tedious and subjective task of manually defining features. Since deep learning is motivated to deal with problems that are very different from the problem of vulnerability detection, we need some guiding principles for applying deep learning to vulnerability detection. In particular, we need to find representations of software programs that are suitable for deep learning. For this purpose, we propose using code gadgets to represent programs and then transform them into vectors, where a code gadget is a number of (not necessarily consecutive) lines of code that are semantically related to each other. This leads to the design and implementation of a deep learning-based vulnerability detection system, called Vulnerability Deep Pecker (VulDeePecker). In order to evaluate VulDeePecker, we present the first vulnerability dataset for deep learning approaches. Experimental results show that VulDeePecker can achieve much fewer false negatives (with reasonable false positives) than other approaches. We further apply VulDeePecker to 3 software products (namely Xen, Seamonkey, and Libav) and detect 4 vulnerabilities, which are not reported in the National Vulnerability Database but were "silently" patched by the vendors when releasing later versions of these products; in contrast, these vulnerabilities are almost entirely missed by the other vulnerability detection systems we experimented with.

Abstract: Neurodegenerative diseases have two general characteristics that are so fundamental we usually take them for granted The first is that the pathology associated with the disease only affects particular neurons (‘selective neuronal vulnerability’); the second is that the pathology worsens with time and impacts more regions in a stereotypical and predictable fashion The mechanisms underpinning selective neuronal and regional vulnerability have been difficult to dissect, but the recent application of whole-genome technologies, the development of mouse models that reproduce spatial and temporal features of the pathology, and the identification of intrinsic morphological, electrophysiological, and biochemical properties of vulnerable neurons are beginning to shed some light on these fundamental features of neurodegenerative diseases Here we detail our emerging understanding of the underlying biology of selective neuronal vulnerability and outline some of the areas in which our understanding is incomplete Neurodegenerative diseases impact specific cell populations within the brain However, not all cells within the population are impacted, a phenomenon called selective cellular vulnerability The molecular basis of this vulnerability is discussed

Abstract: Increasing numbers of software vulnerabilities are discovered every year whether they are reported publicly or discovered internally in proprietary code. These vulnerabilities can pose serious risk of exploit and result in system compromise, information leaks, or denial of service. We leveraged the wealth of C and C++ open-source code available to develop a largescale function-level vulnerability detection system using machine learning. To supplement existing labeled vulnerability datasets, we compiled a vast dataset of millions of open-source functions and labeled it with carefully-selected findings from three different static analyzers that indicate potential exploits. Using these datasets, we developed a fast and scalable vulnerability detection tool based on deep feature representation learning that directly interprets lexed source code. We evaluated our tool on code from both real software packages and the NIST SATE IV benchmark dataset. Our results demonstrate that deep feature representation learning on source code is a promising approach for automated software vulnerability detection.

Abstract: California is a global leader in the agricultural sector and produces more than 400 types of commodities. The state produces over a third of the country’s vegetables and two-thirds of its fruits and nuts. Despite being highly productive, current and future climate change poses many challenges to the agricultural sector. This paper provides a summary of the current state of knowledge on historical and future trends in climate and their impacts on California agriculture. We present a synthesis of climate change impacts on California agriculture in the context of: (1) historic trends and projected changes in temperature, precipitation, snowpack, heat waves, drought, and flood events; and (2) consequent impacts on crop yields, chill hours, pests and diseases, and agricultural vulnerability to climate risks. Finally, we highlight important findings and directions for future research and implementation. The detailed review presented in this paper provides sufficient evidence that the climate in California has changed significantly and is expected to continue changing in the future, and justifies the urgency and importance of enhancing the adaptive capacity of agriculture and reducing vulnerability to climate change. Since agriculture in California is very diverse and each crop responds to climate differently, climate adaptation research should be locally focused along with effective stakeholder engagement and systematic outreach efforts for effective adoption and implementation. The expected readership of this paper includes local stakeholders, researchers, state and national agencies, and international communities interested in learning about climate change and California’s agriculture.

Abstract: Globally, environmental disasters impact billions of people and cost trillions of dollars in damage, and their impacts are often felt most acutely by minority and poor communities. Wildfires in the U.S. have similarly outsized impacts on vulnerable communities, though the ethnic and geographic distribution of those communities may be different than for other hazards. Here, we develop a social-ecological approach for characterizing fire vulnerability and apply it to >70,000 census tracts across the United States. Our approach incorporates both the wildfire potential of a landscape and socioeconomic attributes of overlying communities. We find that over 29 million Americans live with significant potential for extreme wildfires, a majority of whom are white and socioeconomically secure. Within this segment, however, are 12 million socially vulnerable Americans for whom a wildfire event could be devastating. Additionally, wildfire vulnerability is spread unequally across race and ethnicity, with census tracts that were majority Black, Hispanic or Native American experiencing ca. 50% greater vulnerability to wildfire compared to other census tracts. Embracing a social-ecological perspective of fire-prone landscapes allows for the identification of areas that are poorly equipped to respond to wildfires.

Abstract: Climate Change 2007 – Impacts, Adaptation and Vulnerability provides the most comprehensive and up-to-date scientific assessment of the impacts of climate change, the vulnerability of natural and human environments, and the potential for response through adaptation. The report: • evaluates evidence that recent observed changes in climate have already affected a variety of physical and biological systems and concludes that these effects can be attributed to global warming; • makes a detailed assessment of the impacts of future climate change and sea-level rise on ecosystems, water resources, agriculture and food security, human health, coastal and low-lying regions and industry and settlements; • provides a complete new assessment of the impacts of climate change on major regions of the world (Africa, Asia, Australia/New Zealand, Europe, Latin America, North America, polar regions and small islands); • considers responses through adaptation; • explores the synergies and trade-offs between adaptation and mitigation; • evaluates the key vulnerabilities to climate change, and assesses aggregate damage levels and the role of multiple stresses. This latest assessment by the IPCC will form the standard scientific reference for all those concerned with the consequences of climate change, including students and researchers in ecology, biology, hydrology, environmental science, economics, social science, natural resource management, public health, food security and natural hazards, and policymakers and managers in governments, industry and other organisations responsible for resources likely to be affected by climate change

Abstract: Climate change has far-reaching impacts on ecosystems. Recent attempts to quantify such impacts focus on measuring exposure to climate change but largely ignore ecosystem resistance and resilience, which may also affect the vulnerability outcomes. In this study, the relative vulnerability of global terrestrial ecosystems to short-term climate variability was assessed by simultaneously integrating exposure, sensitivity, and resilience at a high spatial resolution (0.05°). The results show that vulnerable areas are currently distributed primarily in plains. Responses to climate change vary among ecosystems and deserts and xeric shrublands are the most vulnerable biomes. Global vulnerability patterns are determined largely by exposure, while ecosystem sensitivity and resilience may exacerbate or alleviate external climate pressures at local scales; there is a highly significant negative correlation between exposure and sensitivity. Globally, 61.31% of the terrestrial vegetated area is capable of mitigating climate change impacts and those areas are concentrated in polar regions, boreal forests, tropical rainforests, and intact forests. Under current sensitivity and resilience conditions, vulnerable areas are projected to develop in high Northern Hemisphere latitudes in the future. The results suggest that integrating all three aspects of vulnerability (exposure, sensitivity, and resilience) may offer more comprehensive and spatially explicit adaptation strategies to reduce the impacts of climate change on terrestrial ecosystems.

Abstract: Poverty has been declining in Sub-Saharan Africa, but millions are still poor or vulnerable. To address this ongoing and complex problem, all countries in the region have now deployed social safety net programs as part of their core development plans. The number of programs has skyrocketed since the mid-2000s, although many interventions are still modest in size. This notable shift in social policy reflects an embrace of the role that social safety nets can play in the fight against poverty and vulnerability, and more generally in building human capital and spurring economic growth. Realizing the Full Potential of Social Safety Nets in Africa provides evidence that positive impacts on equity, resilience, and opportunity are growing, and it is clear that these programs can be good investments. For the potential of social safety nets to be realized, however, they need to expand with smart technical and design choices. Beyond technical considerations, and at least as important, this book argues that a series of decisive shifts needs to occur in three critical spheres: political, institutional, and financial: First, to recognize the role of politics in offering opportunities for expansion and in guiding design and program choice; Second, to anchor safety net programs in strong institutional arrangements that facilitate their expansion and sustainability; And third, to build sustainable financing through greater efficiency, more varied and predictable resources, and shock-responsive resources. Ignoring these spheres may lead to technically sound, but practically impossible, choices and designs. A deliberate focus on these areas is essential if social safety nets are to be brought to scale and sustained at scale. Only then will their full potential and their contribution to the fight against poverty and vulnerability be realized.

Abstract: Flood and flood-related problems have become more rampant all over the world leading to loss of life, infrastructure damage, and epidemics every year. There are evidences in recent years where heavy precipitation events have resulted in severe detrimental floods in India. A number of major cities in India have reported a series of devastating floods in the recent decade. The immediate impact of floods specifically in urban areas is on the transport system. Most of the studies on transport vulnerability consider topographic properties along with supply and demand side of transport system to access the disruption; but less attention is given to the potential impacts of weather extremes on the performance of transportation network. In response to that, this study aims to provide a framework to assess the vulnerability of urban road network due to floods. An integrated framework linking meteorological information, land use functions, and hydrodynamic model with safety speed function is used to relate flood depth to reduction in speed in order to determine road network vulnerability. Two rainfall events with 1-in-10 year and 1-in-100 year return period were simulated for inundation mapping over road network and spatial vulnerability of road network was assessed. A critical map and index is developed to identify affected road length vulnerable to flood. It has been observed that more than 40% of road length across the network becomes immovable for 1-in-100 year rainfall event. Also, there is a significant decrease in average maximum speed in each road category corresponding to its normal.

Abstract: Climate change is adversely affecting smallholder farming households in Africa and in particular in Ghana because their activity depends on climate-regulated water resources. This study examined the vulnerability of smallholder maize farming households to climate change in the Brong-Ahafo region of Ghana by employing the Livelihood Vulnerability Index with particular emphasis on access to and utilization of water resources. The primary data were based on 150 maize farming households, complemented by secondary data on rainfall and temperature over the period 1983–2013. To assess the climate change effects and related vulnerability, a comparative analysis was performed for the Wenchi and Techiman municipalities in the Brong-Ahafo region. The empirical results revealed that farming households in Wenchi municipality were more vulnerable to climate change and weather variability in terms of food, water, and health than those in Techiman municipality. Furthermore, farming households in Wenchi municipality were more vulnerable in terms of adaptive capacity, taking into account the socio-demographic aspects, social networks, and livelihoods of households in the municipality than those in Techiman municipality. These results have implications for the initiation and implementation of climate change adaptation and household resilience projects by the government, donor agencies, and other related organizations in the two municipalities in the region.

Abstract: Pakistan is alarmingly exposed and vulnerable to flood disasters as a result of rapid urbanization that has not taken into account the threats posed by climate change. The devastating impacts of floods and other natural disasters put extra pressure on the country’s budget and has driven the country’s leadership to adopt a proactive approach instead of traditional, aid-based, approach, one that encourages the inclusion of disaster risk reduction measures within local disaster management policies. This research elaborates household vulnerability and resilience to flood disaster within two districts within Pakistan. It uses a dataset of 600 households collected through face-to-face interviews from two districts within the Khyber Pakhtunkhwa province that were severely affected by the 2010 flood and data from the Directorate of Khyber Pakhtunkhwa Provincial Disaster Management Authority. In a second step, we assigned weights to the selected variables for vulnerability (exposure, susceptibility and adaptive capacity) and resilience (with social, physical, economic, and institutional components) and used a subjective method (based on expert judgment) to weight these. The survey findings revealed that both study areas were highly vulnerable and had low resilience to flood disasters. The study findings indicated that community households in the flood-prone areas of Nowshera district were more vulnerable and less resilient than those in Charsadda, with a higher composite vulnerability index scoring and a lower composite resilience index score. This study shows that provincial and local disaster management authorities can play a vital role in reducing vulnerability and that more efforts are required to strengthen social, physical, economic, and institutional resilience through capacity-building training, preparedness, and awareness building about preventing and mitigating flood damage.

Abstract: The evolution and sophistication of cyber-attacks need resilient and evolving cybersecurity schemes As an emerging technology, the Internet of Things (IoT) inherits cyber-attacks and threats from the IT environment despite the existence of a layered defensive security mechanism The extension of the digital world to the physical environment of IoT brings unseen attacks that require a novel lightweight and distributed attack detection mechanism due to their architecture and resource constraints Architecturally, fog nodes can be leveraged to offload security functions from IoT and the cloud to mitigate the resource limitation issues of IoT and scalability bottlenecks of the cloud Classical machine learning algorithms have been extensively used for intrusion detection, although scalability, feature engineering efforts, and accuracy have hindered their penetration into the security market These shortcomings could be mitigated using the deep learning approach as it has been successful in big data fields Apart from eliminating the need to craft features manually, deep learning is resilient against morphing attacks with high detection accuracy This article proposes an LSTM network for distributed cyber-attack detection in fog-to-things communication We identify and analyze critical attacks and threats targeting IoT devices, especially attacks exploiting vulnerabilities of wireless communications The conducted experiments on two scenarios demonstrate the effectiveness and efficiency of deeper models over traditional machine learning models

Abstract: The Intergovernmental Panel on Climate Change (IPCC) periodically develops an assessment of the state of the climate. The report was developed in 2012, including a new section on climate adaptation. The report integrates perspectives from several historically distinct research communities studying climate science, climate impacts, adaptation to climate change, and disaster risk management. Climate extremes, exposure, and vulnerability are influenced by a wide range of factors, including anthropogenic climate change, natural climate variability, and socio-economic development. The impacts of climate extremes and the potential for disasters result from the climate extremes themselves and from the exposure and vulnerability of human and natural systems. Economic losses from weather- and climate-related disasters have increased, but with large spatial and inter-annual variability. Adaptation to climate change and disaster risk management provides a range of complementary approaches for managing the risks of climate extremes and disasters.

Abstract: As globalization and other pressures intensify the economic, social and biophysical connections between people and places, it seems likely that adaptation responses intended to ameliorate the impacts of climate change might end up shifting risks and vulnerability between people and places. Building on earlier conceptual work in maladaptation and other literature, this article explores the extent to which concerns about vulnerability redistribution have influenced different realms of adaptation practice. The review leads us to conclude that the potential for adaptation to redistribute risk or vulnerability is being given only sparse—and typically superficial—attention by practitioners. Concerns about ‘maladaptation’, and occasionally vulnerability redistribution specifically, are mentioned on the margins but do not significantly influence the way adaptation choices are made or evaluated by policy makers, project planners or international funds. In research, the conceptual work on maladaptation is yet to translate into a significant body of empirical literature on the distributional impacts of real-world adaptation activities, which we argue calls into question our current knowledge base about adaptation. These gaps are troubling, because a process of cascading adaptation endeavors globally seems likely to eventually re-distribute risks or vulnerabilities to communities that are already marginalized and vulnerable. We conclude by discussing the implications that the potential for vulnerability redistribution might have for the governance of adaptation processes, and offer some reflections on how research might contribute to addressing gaps in knowledge and in practice. For further resources related to this article, please visit the WIREs website.

Abstract: Because their assets and income represent such a small share of national wealth, the impacts of climate change on poor people, even if dramatic, will be largely invisible in aggregate economic statistics such as the Gross Domestic Product (GDP). Assessing and managing future impacts of climate change on poverty requires different metrics, and specific studies focusing on the vulnerability of poor people. This special issue provides a set of such studies, looking at the exposure and vulnerability of people living in poverty to shocks and stressors that are expected to increase in frequency or intensity due to climate change, such as floods, droughts, heat waves, and impacts on agricultural production and ecosystem services. This introduction summarizes their approach and findings, which support the idea that the link between poverty and climate vulnerability goes both ways: poverty is one major driver of people's vulnerability to climate-related shocks and stressors, and this vulnerability is keeping people in poverty. The paper concludes by identifying priorities for future research.

Abstract: A growing number of health authorities around the world are conducting climate change and health vulnerability and adaptation assessments; however, few explore impacts and adaptations related to mental health. We argue for an expanded conceptualization of health that includes both the physiological and psychological aspects of climate change and health. Through a review of the global literature on mental health and climate change, this analytical review explores how mental health can be integrated into climate change and health vulnerability assessments and concludes with recommendations for integrating mental health within climate change and health vulnerability and adaptation assessments.

Abstract: "Vulnerability" is a key concept for research ethics and public health ethics. This term can be discussed from either a conceptual or a practical perspective. I previously proposed the metaphor of layers to understand how this concept functions from the conceptual perspective in human research. In this paper I will clarify how my analysis includes other definitions of vulnerability. Then, I will take the practical-ethical perspective, rejecting the usefulness of taxonomies to analyze vulnerabilities. My proposal specifies two steps and provides a procedural guide to help rank layers. I introduce the notion of cascade vulnerability and outline the dispositional nature of layers of vulnerability to underscore the importance of identifying their stimulus condition. In addition, I identify three kinds of obligations and some strategies to implement them. This strategy outlines the normative force of harmful layers of vulnerability. It offers concrete guidance. It contributes substantial content to the practical sphere but it does not simplify or idealize research subjects, research context or public health challenges.

Abstract: The Paris Agreement binds all nations to undertake ambitious efforts to combat climate change, with the commitment to “hold warming well below 2 °C in global mean temperature (GMT), relative to pre-industrial levels, and to pursue efforts to limit warming to 1.5 °C”. The 1.5 °C limit constitutes an ambitious goal for which greater evidence on its benefits for health would help guide policy and potentially increase the motivation for action. Here we contribute to this gap with an assessment on the potential health benefits, in terms of reductions in temperature-related mortality, derived from the compliance to the agreed temperature targets, compared to more extreme warming scenarios. We performed a multi-region analysis in 451 locations in 23 countries with different climate zones, and evaluated changes in heat and cold-related mortality under scenarios consistent with the Paris Agreement targets (1.5 and 2 °C) and more extreme GMT increases (3 and 4 °C), and under the assumption of no changes in demographic distribution and vulnerability. Our results suggest that limiting warming below 2 °C could prevent large increases in temperature-related mortality in most regions worldwide. The comparison between 1.5 and 2 °C is more complex and characterized by higher uncertainty, with geographical differences that indicate potential benefits limited to areas located in warmer climates, where direct climate change impacts will be more discernible.

Abstract: Nonnuclear weapons are increasingly able to threaten dual-use command, control, communication, and intelligence assets that are spaced based or distant from probable theaters of conflict. This form...