Subjects -> HEALTH AND SAFETY (Total: 1508 journals)
    - CIVIL DEFENSE (22 journals)
    - DRUG ABUSE AND ALCOHOLISM (86 journals)
    - HEALTH AND SAFETY (704 journals)
    - WOMEN'S HEALTH (82 journals)

CIVIL DEFENSE (22 journals)

Showing 1 - 22 of 22 Journals sorted alphabetically
Aggression and Violent Behavior     Hybrid Journal   (Followers: 482)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 47)
Disaster Health     Hybrid Journal   (Followers: 1)
Disaster Recovery Journal     Full-text available via subscription   (Followers: 3)
Disasters     Hybrid Journal   (Followers: 18)
Emergency Services SA     Full-text available via subscription   (Followers: 2)
Evolution, Medicine, and Public Health     Open Access   (Followers: 12)
Global & Regional Health Technology Assessment     Open Access   (Followers: 1)
International Journal of Critical Infrastructure Protection     Hybrid Journal   (Followers: 7)
International Journal of Emergency Management     Hybrid Journal   (Followers: 12)
International Journal of Forensic Engineering     Hybrid Journal   (Followers: 3)
International Journal of Intelligent Defence Support Systems     Hybrid Journal   (Followers: 5)
Journal of Applied Security Research     Hybrid Journal   (Followers: 5)
Journal of Health Care Law and Policy     Open Access   (Followers: 4)
Journal of Homeland Security and Emergency Management     Hybrid Journal   (Followers: 11)
Journal of Positive Psychology and Wellbeing     Open Access   (Followers: 5)
Korean Journal of Defense Analysis     Hybrid Journal  
Prehospital and Disaster Medicine     Full-text available via subscription   (Followers: 9)
Revista Internacional de la Cruz Roja     Full-text available via subscription   (Followers: 2)
Risk, Hazards & Crisis in Public Policy     Hybrid Journal   (Followers: 6)
Strategic Analysis     Hybrid Journal   (Followers: 6)
Studies in Conflict & Terrorism     Hybrid Journal   (Followers: 501)
Similar Journals
Journal Cover
International Journal of Critical Infrastructure Protection
Journal Prestige (SJR): 0.648
Citation Impact (citeScore): 2
Number of Followers: 7  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1874-5482 - ISSN (Online) 1874-5482
Published by Elsevier Homepage  [3204 journals]
  • Resilience for whom' The general public's tolerance levels as CI
           resilience criteria
    • Abstract: Publication date: Available online 26 February 2020Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Laura Petersen, Emma Lundin, Laure Fallou, Johan Sjöström, David Lange, Rui Teixeira, Alexandre Bonavita
  • Generating Invariants using Design and Data-centric Approaches for
           Distributed Attack Detection
    • Abstract: Publication date: Available online 22 February 2020Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Muhammad Azmi Umer, Aditya Mathur, Khurum Nazir Junejo, Sridhar Adepu A cyber attack launched on a critical infrastructure (CI), such as a power grid or a water treatment plant, could lead to anomalous behavior. There exist several methods to detect such behavior. This paper reports on a study conducted to compare two methods for detecting anomalies in CI. One of these methods, referred to as design-centric, generates invariants from the design of a CI. Another method, referred to as data-centric, generates the invariants from data collected from an operational CI. The key question that motivated the study is “How do design and data-centric methods compare in the effectiveness of the generated invariants in detecting process anomalies.” The data-centric approach used Association Rule Mining for generating invariants from operational data. These invariants, and their performance in detecting anomalies, was compared against those generated by a design-centric approach reported in the literature. The entire study was conducted in the context of an operational scaled down version of a water treatment plant.
  • A Methodology for Security Classification applied to Smart Grid
    • Abstract: Publication date: Available online 17 February 2020Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Manish Shrestha, Christian Johansen, Josef Noll, Davide Roverso The electricity grid is an important critical infrastructure that is undergoing major changes, due to the Internet of Things (IoT) and renewable energy, heading towards the smart grid. However, besides the many good promises of the smart grid, such as better peak control, cheaper maintenance, and more open energy markets, there are many new security threats evolving, especially from the IoT side, and also from the diversification of the systems and practices that the smart grid brings. We thus see the need for more light-weight and dynamic methods for conducting security analyses of systems applicable at (re)design time, intended to help system engineers build secure systems from the start. As a consequence, the methods should also look more at the functionalities (exposure/protection) of the system than at the possible attacks. In this paper we propose a methodology called Smart Grid Security Classification (SGSC) developed for complex systems like the smart grid, focusing on the specifics of Advanced Metering Infrastructure (AMI) systems. Our methodology is built upon the Agence nationale de la sécurité des systémes d’information (ANSSI) standard methodology for security classification of general Information and Communication Systems (ICS). Analyses performed following our method easily translate into ANSSI valid reports. Our SGSC is related to methods of risk analysis with the difference that our classification method has the purpose to assign a system to a security class, based on (combinations of) scores given to the various exposure aspects of the system and the respective protection mechanisms implemented; without looking at attackers. There are multiple uses of SGSC, such as offering indications to decision-makers about the security aspects of a system and for deciding purchasing strategies, for regulatory bodies to certify various complex infrastructure systems, but also for system/security designers to make easier choices of correct functionalities that would allow to reach a desired level of security. Particularly useful for smart grid systems is the discussion and mapping that we do of the SGSC methodology to a complex AMI infrastructure description derived from real deployments being done in ongoing Norwegian smart grid upgrades.
  • Seismic risk assessment of natural gas networks with steady-state flow
    • Abstract: Publication date: Available online 11 February 2020Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Francesco Cavalieri Natural gas networks are spatially distributed systems that play a crucial role in the well-being and safety of communities. Most of the works in the current literature analyse natural gas systems only in topological terms. However, the low tolerance on amount and pressure of gas fed to end-users for maintaining serviceability generates the need for a capacitive analysis. The latter includes connectivity and involves computation of the system's operational state, in terms of pipe flows and node pressures. The paper presents a comprehensive methodology for the seismic risk assessment of gas transmission and distribution networks. The seismic hazard, the vulnerability assessment and the evaluation of the system's performance are addressed with a simulation-based approach, accounting for the relevant uncertainties. The use of the capacitive analysis in this scope represents the most important feature of this work: a complete steady-state flow formulation is used, encompassing multiple pressure levels, the pressure-driven mode and the correction for pipe elevation change. The presented methodology has been implemented into an open-source software, OOFIMS, and applied to a realistic benchmark network composed of 135 nodes and 170 edges, thus resulting to be usable by emergency managers and stakeholders engaged in increasing the seismic resilience of communities.
  • Using stakeholders’ Judgement and Fuzzy Logic Theory to Analyze the Risk
           Influencing Factors in Oil and Gas Pipeline Projects: Case Study in Iraq,
           Stage II
    • Abstract: Publication date: Available online 7 February 2020Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Layth Kraidi, Raj Shah, Wilfred Matipa, Fiona Borthwick Oil and gas pipelines are safe and economic to petroleum products transportation. Nevertheless, enormous risk influencing factors are threatening the safety of these pipelines during the planning, construction and operations stages of these projects. Risk analysis in these projects is hindered by the inaccurate data about the probability and severity levels of the risk influencing factors. This problem is exacerbated further in troubled and developing countries, where the documentations and records are not at the best conditions. This study aims to identify and analyze potential risk influencing factors using a more integrated risk analysis framework. In this a such framework, the critical risk influencing factors and some of applied risk mitigation methods were identified based on a comprehensive review of pipelines projects worldwide. The impact of the identified factors and the effectiveness of mitigation methods were evaluated based on an industry-wide questionnaire survey, which was conducted in Iraq. A Computer-Based Risk Analysis Model (CBRAM) was designed to analyze the risk influencing factors using a fuzzy logic theory to consider any uncertainty that is associated with stakeholders’ judgments and data scarcity. The CBRAM has confirmed the most critical risk influencing factors, which this study has explained the effective methods to manage them.
  • Multi-Criteria Node Criticality Assessment Framework for Critical
           Infrastructure Networks
    • Abstract: Publication date: Available online 1 February 2020Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Luca Faramondi, Gabriele Oliva, Roberto Setola Spotting criticalities in Critical Infrastructure networks is a crucial task in order to implement effective protection strategies against exogenous or malicious events. Yet, most of the approaches in the literature focus on specific aspects (e.g., presence of hubs, minimum paths) and there is a need to identify tradeoffs among importance metrics that are typically clashing with each other. In this paper we propose an approach for the assessment of criticalities which combines multi-criteria decision making techniques and topological/dynamical centrality measures. In particular, we resort to the Sparse Analytic Hierarchy Process (SAHP) technique to calculate the relevance of the different metrics based on pairwise comparisons of the metrics by Subject Matter Experts (SMEs) and to merge the different metrics into a holistic indicator of node criticality/importance that takes into account all the metrics. With the aim to experimentally demonstrate the potential of the proposed approach, we consider a case study related to the Central London Tube Network. According to the experimental results, the proposed aggregated ranking exhibits negligible correlation with the single metrics being aggregated, thus suggesting that the proposed approach effectively combines the different metrics into a new perspective.
  • A new soft computing approach for analyzing the influential relationships
           of critical infrastructures
    • Abstract: Publication date: Available online 26 December 2019Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Huai-Wei Lo, James J.H. Liou, Chun-Nen Huang, Yen-Ching Chuang, Gwo-Hshiung TzengAbstractApproaches to risk assessment for the protection and management of critical infrastructures must continue to evolve to address uncertainty and hazards that may be encountered in the future. Extreme climate change and accidents arising from human activity increasingly threaten critical infrastructures. There are two vital issues to consider when protecting critical infrastructures: their interdependencies and priorities. We propose a novel hybrid multi-criteria decision-making model for uncertain environments, derived from the opinions of multiple experts, capable of building an influence network relationship and analyzing the influence and importance of critical infrastructures. The proposed model overcomes the problems caused by the diverse of opinions of experts arising from inherent conflicts due to their different backgrounds. The proposed model maps out the interdependencies and priorities among critical infrastructures in a complex system. The model developed in this study can support decision-makers and regulatory agencies when deciding upon appropriate protection plans. The effectiveness of the proposed model is demonstrated by conducting a case study involving Taiwan. The results indicate that the proposed model can effectively assist managers to evaluate the influential relationships among critical infrastructures and identify those which are most critical.
  • IJCIP Editorial December 2019 – Volume 27
    • Abstract: Publication date: December 2019Source: International Journal of Critical Infrastructure Protection, Volume 27Author(s): Leon Strous
  • Measures of Robustness for Networked Critical Infrastructure: an Empirical
           Comparison on Four Electrical Grids
    • Abstract: Publication date: Available online 20 November 2019Source: International Journal of Critical Infrastructure ProtectionAuthor(s): John W. Galbraith, Luca IulianiAbstractEvaluating the robustness of critical infrastructure is important for good decisions and for communicating progress toward greater robustness. Nonetheless there is no widely accepted measure analogous to readily available measures of cost-efficiency; our aim here is to examine the usefulness of some candidate robustness measures. A number of possible choices can be computed based on different principles including network topology, entropy and direct estimation of cumulative maximum capacity loss, and measures based on the latter principles are suggested here. To judge their usefulness we introduce the required-capacity survival function and compute this function on representations of four electrical grids, together with a set of scalar robustness measures, conditional on publicly available information. We then evaluate the degree to which the scalar measures provide adequate summary indicators of the more comprehensive capacity-loss information revealed in the survival functions. The measures produce substantially different results, and we find in particular that topological measures correspond only weakly with cumulative capacity loss from destructive events.
  • A Leakage Risk Assessment Method for Hazardous Liquid Pipeline Based on
           Markov Chain Monte Carlo
    • Abstract: Publication date: Available online 14 November 2019Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Zhengbing Li, Huixia Feng, Yongtu Liang, Ning Xu, Siming Nie, Haoran ZhangAbstractPipeline is now a commonly-used transportation mode for hazardous liquid, whereas followed by frequent pipeline leakage accidents. Research on the leakage post-assessment of hazard liquid pipeline has received increasing attention, but the in-situ data are hard to be accurately captured, resulting in a series of uncertainties affecting the accuracy and practicality of the risk assessment. This paper puts forward a novel method, which is able to accurately achieve leakage detection, cause analysis and leakage volume forecast by avoiding deviation of in-situ data, model parameters and the uncertainties caused by method, thereby quickly assessing the impact on the surrounding environment. The Markov Chain Monte Carlo (MCMC) algorithm is employed for repeatedly sampling leakage position and coefficient, furthermore, the transient hydrothermal and the leakage risk assessment model are established for determining the leakage volume and the risk grade. The influence of real-time measurement data and the deviation of the method are taken into consideration through the frequency distribution statistics of numerous sampling data. Based on two real examples, it is verified that the risk assessment method has practical value for the in-situ analysis and emergency treatment.
  • A Method for Testing Distributed Anomaly Detectors
    • Abstract: Publication date: Available online 15 October 2019Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Gayathri Sugumar, Aditya MathurAbstractDistributed anomaly detectors are deployed in critical infrastructure to raise alerts when the underlying plant deviates from its expected behaviour. A novel method, referred to as SCM, that uses well defined state and command mutation operators, is proposed to test such detectors prior to their deployment. Cyber-attacks, each modelled as a timed-automaton, serve as reference attacks. A potentially large set of attacks is then created by systematically applying the mutation operators to each reference attack. In a case study, SCM was applied to a timed-automata model of a water treatment plant to assess its effectiveness in testing a distributed anomaly detector. Results attest to the value of SCM in identifying weaknesses in an anomaly detector, prior to its deployment, and improving its effectiveness in detecting process anomalies.
  • A Novel Online State-Based Anomaly Detection System for Process Control
    • Abstract: Publication date: Available online 31 August 2019Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Hamed Farsi, Ali Fanian, Zahra TaghiyarrenaniAbstractIndustrial control networks are the core part of critical infrastructures such as power grid and oil refinery. In recent years, the number of cyber-attacks to industrial control networks are growing increasingly. Moreover, connecting industrial networks to the public network makes these critical infrastructures more vulnerable to the cyber-attacks. Therefore, improving the security of these networks has attracted much attention nowadays. To protect industrial control networks, the proposed online method is able to detect anomalies with low computational time while do not use prior knowledge about the system and anomalies. This method can adjust the severity of detection in order to efficiently detect changes which lead to anomalies; And also can be adapted to inevitable network changes by updating the anomaly threshold using the latest normal states. The proposed method finds anomalies in the network using high-pass filters and Euclidean distance of the current state with the latest states. To evaluate the efficiency of the proposed approach, a boiler control system is simulated and three test datasets are provided from this simulation. The proposed intrusion detection system was evaluated through these datasets, as well as the SWaT dataset. The results show that the proposed approach not only is highly effective for detecting anomalies, but also is adaptable to the normal variations in the network.
  • Critical Rotating Machinery Protection by Integration of a
           “Fuse” Bearing
    • Abstract: Publication date: Available online 6 June 2019Source: International Journal of Critical Infrastructure ProtectionAuthor(s): Dmitri Gazizulin, Evyatar Cohen, Jacob Bortman, Renata KleinAbstractMinimizing physical damage to mechanical equipment caused by cyber-attacks is currently a challenge. This work describes a new concept for protecting critical mechanical systems against such attacks in which a defense layer is added to the critical rotating machine to prevent hostile entities from damaging it. The machine includes a mechanical component – a rolling element bearing (REB) – which acts as a “fuse” mechanism. It is designed so that under cyber-attack the “fuse” REB will be damaged first, ahead of other critical components. Moreover, the defense layer includes condition monitoring (CM) tools designed for the “fuse” REB. As far as we know, this is the first work that shows how CM tools can be used as a protective layer against cyber-attack. This study describes the design concepts and focuses on early fault detection and condition monitoring solutions via vibration analysis. Endurance tests were conducted to demonstrate the feasibility of the proposed concept and yield insights into the analysis process of the failure modes that were developed in the “fuse” REB.
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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