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Car manufacturers are noticing and encouraging a trend away from individual mobility, where a vehicle is owned and driven by one or only a few other persons, and towards shared-mobility concepts. That means that many different people use and have access to the same vehicle. An attacker disguised as a regular short-time user can use the additional attack vectors (s)he gets by having physical access to tamper the vehicle’s software. The software takes a continuously more crucial role in cars for autonomous driving, and manipulations can have catastrophic consequences for the persons on board. Currently, there is no mechanism available to the vehicle owner to detect such manipulations in the vehicle done by the attacker (short-time user). In this work, a novel vehicle attestation scheme called Vehicular Soft Integrity Preservation Scheme (VeSIPreS) is proposed to detect tampering in the software stack of a vehicle and guarantee the upcoming driver that the previous user has not changed the software of the vehicle. The solution consists of a software module in the vehicle and a mobile-based user application for the vehicle owner to monitor the vehicle’s soft integrity. Inside the vehicle, the software module is implemented in the central gateway, which acts as the primary security component. VeSIPreS uses Trusted Platform Module (TPM) in the central gateway, which anchors trust in our proposed solution. This paper also provides a proof-of-concept implementation with a TPM, demonstrating its application and deployment feasibility and presentig a security analysis to show the security of VeSIPreS.

Vehicular ad hoc networks (VANETs) have no fixed infrastructure and instead relies on the vehicles themselves to provide network functionality. An attack scenario with potentially catastrophic consequences is the outbreak of mobile worm epidemic in these networks. This paper analyses the snapshot spreading results under an urban scenario with equilibrium traffic through modelling the mobility pattern, the communication channel, the medium access control (MAC) mechanism and the worm propagation process. The extensive Monte Carlo simulations uncovered the effects of the transmission range (from a typical minimum to a maximum), the minimum velocity and the maximum velocity (from the free flow to the congested traffic), the vehicle density (from a sparse topology to a dense spatial relation) and the MAC mechanism (from presence to absence) on epidemic spreading of such worms in VANETs. Furthermore, the authors simulate the wireless worm propagation in dynamic traffic with the same scenario as the static traffic by using a network simulation tool. The authors discuss the correlation between snapshot results and evolutive outcome, also analyse the reasons resulting in the local differences and finally uncover the interrelations between the affected rate and network parameters. The results are expected to help engineers design intelligent and automatic detection prevention strategies for VANETs.

Experiencing both recurrent small-scale events as well as devastating large-scale catastrophes, no other region in the world is affected by disasters as is East Asia and the Pacific. In the last decade, Ho Chi Minh City, Jakarta, Manila, and many other cities have been repeatedly hit by floods. In the last five years, Asia has experienced a large share of wide-scale natural catastrophes, including earthquakes in the Tohoku region in 2011, Padang in 2009, and Wenchuan in 2008; typhoons in 2009 in the Lao People's Democratic Republic, the Philippines, and Vietnam; a cyclone in Myanmar in 2008; and large-scale floods in 2011 in Cambodia, Thailand, and the Philippines. The year 2011 was the costliest year on record for natural disasters with cascading effects (Japan) and trans-boundary consequences (Thailand), adding up to US

Different points of view have been put forward concerning the creation of value and the results obtained through mergers/acquisitions, along with their interpretation. Mergers/acquisitions may constitute a means of rapid growth, but they may also have catastrophic consequences. This chapter discusses a variety of definitions of performance, synergy and value creation, alongside the positive and negative effects of mergers/acquisitions. It identifies determiners leading to improved or reduced performance, and the reasons for negative outcomes. Shih took a similar view, studying the fiscal motivation involved in conglomerate mergers/acquisitions where there was little correlation between the profits of the firms participating in the merger. The work of Pettway and Trifts and Mathur and De forms a useful starting point in demonstrating poor performance in mergers/acquisitions. These authors observed that abnormal returns become negative over time, notably for the buyer.

Purpose The purpose of this paper is to explain to readers how intelligent systems can fail and how artificial intelligence (AI) safety is different from cybersecurity. The goal of cybersecurity is to reduce the number of successful attacks on the system; the goal of AI Safety is to make sure zero attacks succeed in bypassing the safety mechanisms. Unfortunately, such a level of performance is unachievable. Every security system will eventually fail; there is no such thing as a 100 per cent secure system. Design/methodology/approach AI Safety can be improved based on ideas developed by cybersecurity experts. For narrow AI Safety, failures are at the same, moderate level of criticality as in cybersecurity; however, for general AI, failures have a fundamentally different impact. A single failure of a superintelligent system may cause a catastrophic event without a chance for recovery. Findings In this paper, the authors present and analyze reported failures of artificially intelligent systems and extrapolate our analysis to future AIs. The authors suggest that both the frequency and the seriousness of future AI failures will steadily increase. Originality/value This is a first attempt to assemble a public data set of AI failures and is extremely valuable to AI Safety researchers.

Purpose This paper aims to formalize long-term trajectories of human civilization as a scientific and ethical field of study. The long-term trajectory of human civilization can be defined as the path that human civilization takes during the entire future time period in which human civilization could continue to exist. Design/methodology/approach This paper focuses on four types of trajectories: status quo trajectories, in which human civilization persists in a state broadly similar to its current state into the distant future; catastrophe trajectories, in which one or more events cause significant harm to human civilization; technological transformation trajectories, in which radical technological breakthroughs put human civilization on a fundamentally different course; and astronomical trajectories, in which human civilization expands beyond its home planet and into the accessible portions of the cosmos. Findings Status quo trajectories appear unlikely to persist into the distant future, especially in light of long-term astronomical processes. Several catastrophe, technological transformation and astronomical trajectories appear possible. Originality/value Some current actions may be able to affect the long-term trajectory. Whether these actions should be pursued depends on a mix of empirical and ethical factors. For some ethical frameworks, these actions may be especially important to pursue.

Chemical, biological, radiological, and nuclear (CBRN) events can take a catastrophic toll on human life, the environment, and the economy. This article first presents the beginnings of a framework for the analysis of behavioral aspects of population mobility in the aftermath of a CBRN event in terms of four phases: quarantine, evacuation, resettlement, and return. Population movements are often omitted from economic consequence analyses because of the difficulty of conceptualizing and estimating them. Through a synthesis of the literature in the context of our analytical framework, we provide estimates of the drivers of important dimensions of population mobility relating to compliance, geography, and timing for each major threat type. We also provide an assessment of error bounds on these estimates. Our findings indicate that omission of various dimensions of population mobility can lead to the underestimation of economic consequences of CBRN events by one or two orders of magnitude. The analysis is intended to point out the relative sensitivities of bottom-line economic impacts to the various population mobility dimensions, so as to guide researchers undertaking this estimation and to help prioritize future research on reducing uncertainties in the direction of drivers that are the most impactful.

The core of a system of protection and safety in workplaces is to identify the hazards and assess the risks to safety and health of workers and population. Directive 2013/59/Euratom for radiation protection requires an assessment of potential emergency exposure situations and associated public and occupational exposures. This kind of assessment involves the identification of maximum-credible accident scenarios. In the healthcare sector, radioactive substances are used both in vivo and in vitro for diagnostic and therapeutic purposes. The main applications take place in Nuclear Medicine Departments, where unsealed radioactive materials for the preparation of radiopharmaceuticals and liquid radioactive waste produced by excreta of patients are present. In this context, flooding is an event that can become critical when the cause is internal to the hospital or catastrophic when it is external: such cases are now statistically more and more relevant due to the overall increase all around the world of extreme weather events, and Nuclear Medicine Departments show a high degree of vulnerability and exposure due to the presence and utilization of unsealed radioactive substance in high-density population areas. In the present work, different scenarios of flooding leading to a potential radiological emergency inside a Nuclear Medicine Department are discussed, both in radiopharmacy laboratories and in the areas for the storage of liquid radioactive waste from diagnostic and therapeutic units. The risk assessment is conducted, evaluating the dispersion of the radioactive materials involved and the resulting exposure of emergency workers and of the representative person in the population. Finally, suitable measures to respond to the emergency are suggested.

A dam-break flood can cause catastrophic life losses due to the uncontrolled large amount of water. This paper aims to improve the estimation of loss of life (LOL) from dam failure in China. For this purpose, we collect fifteen dam failure cases in China. Each failure case is further divided into subcases, if possible, based on flood severity and distance between the flooded area and the dam site. As a result, there are totally twenty-two subcases. Using the subcases as the basic data, an improved method is proposed for determining LOL that occurred from dam break by dividing the flood severity into two conditions: low flood severity, and medium and high flood severity. Correspondingly, two empirical equations are developed based on the multi-variable regression analysis for low flood severity, and medium and high flood severity, respectively. The proposed equations can predict a range for fatality rates from 0.0 to 1.0, and thus it can be applied for any case with any fatality rate. A comparison between the proposed equations and other methods is carried out, which shows that the proposed equations are much closer to the actual values with a coefficient of determination (R2) equals 0.9848, and 0.9872 for low flood severity equation and medium and high flood severity equation, respectively. Furthermore, the proposed empirical equations are applied to predict the life losses of three cases, two cases of low flood severity and one of medium flood severity. The results show a good agreement between the estimated life losses and actual life losses.

The accidental release of toxic gases leads to fire, explosion, and acute toxicity, and may result in severe problems for people and the environment. The risk analysis of hazardous chemicals using consequence modelling is essential to improve the process reliability and safety of the liquefied petroleum gas (LPG) terminal. The previous researchers focused on single-mode failure for risk assessment. No study exists on LPG plant multimode risk analysis and threat zone prediction using machine learning. This study aims to evaluate the fire and explosion hazard potential of one of Asia’s biggest LPG terminals in India. Areal locations of hazardous atmospheres (ALOHA) software simulations are used to generate threat zones for the worst scenarios. The same dataset is used to develop the artificial neural network (ANN) prediction model. The threats of flammable vapour cloud, thermal radiations from fire, and overpressure blast waves are estimated in two different weather conditions. A total of 14 LPG leak scenarios involving a 19 kg capacity cylinder, 21 tons capacity tank truck, 600 tons capacity mounded bullet, and 1350 tons capacity Horton sphere in the terminal are considered. Amongst all scenarios, the catastrophic rupture of the Horton sphere of 1350 MT capacity presented the most significant risk to life safety. Thermal flux of 37.5 kW/ m2 from flames will damage nearby structures and equipment and spread fire by the domino effect. A novel soft computing technique called a threat and risk analysis-based ANN model has been developed to predict threat zone distances for LPG leaks. Based on the significance of incidents in the LPG terminal, 160 attributes were collected for the ANN modelling. The developed ANN model predicted the threat zone distance with an accuracy of R2 value being 0.9958, and MSE being 202.9061 in testing. These results are evident in the reliability of the proposed framework for safety distance prediction. The LPG plant authorities can adopt this model to assess the safety distance from the hazardous chemical explosion based on the prior forecasted atmosphere conditions from the weather department.