An optimization model to inform alternatives for resilient communities for tornado building retrofits

The study describes methods for protecting the critical infrastructure of a state. The article aims to determine the combination of protecting methods of the state’s critical infrastructure from terrorist activities, namely security, physical protection, protection of critical infrastructure, protection of critical information infrastructure, and prevention of emergencies of a terrorist nature at objects of critical infrastructure. It is necessary to fulfil the following objectives to achieve the aim: to consider the difference and interrelation of the concepts of critical infrastructure and information critical infrastructure; to characterise the general properties of various terms, in particular: security, physical protection, protection of critical infrastructure, protection of information critical infrastructure, prevention of terrorist emergencies at objects of critical infrastructure; to analyse from the scientific point of view the classical definitions of forms and methods of critical infrastructure protection; to propose a generalised structure of information and technical methods of critical infrastructure protection; to determine the possibility of using information and technical methods in various fields of knowledge to protect the state’s critical infrastructure from terrorist influence. In summary, the structure of information and technical methods for critical infrastructure protection consists of three components: a mathematical model that describes the process occurring at critical infrastructure, a control algorithm that implements the mathematical model, and procedures that indicate the order of actions for applying the method. The problem of protecting critical infrastructure from terrorist activities requires technical, legal, military, psychological, medical, chemical, biological, and other sciences to address it. Each type of science will use its specific methods to solve practical problems of preventing terrorist emergencies at critical infrastructure. For technical sciences, there will be information-technical, engineering-technical, operational-technical, organisational-technical, biotechnical, and other methods to prevent emergencies of a terroristic nature that need development shortly. Keywords: critical information infrastructure, protection, terror, security, terrorist emergency.

Evaluation of cost-effective building retrofit strategies through soft-linking a metamodel-based Bayesian method and a life cycle cost assessment method

Recent earthquake events have highlighted the importance of critical infrastructure (CI) resilience, as a strong correlation was found between economic loss and severity of CI damage. CIs are characterized by a complex structure composed of sub-components that are essential for the continuous performance of the system. CI owners and governments allocate ample resources to retrofitting and upgrading CI systems and components to increase the resilience of CIs and reduce risk in case of seismic events. Governments and decision makers must manage and optimize the retrofitting efforts to meet budget and time constraints. This research presents a probabilistic methodology for CI seismic risk mitigation and management. The risk expectancy is appraised according to an FTA-based stochastic simulation. The simulation includes the development of exclusive fragility curves for the CI and an examination of the expected damage distribution as a function of earthquake intensity and fragility uncertainty of the components. Furthermore, this research proposes a novel RMIR (risk mitigation to investment ratio) indicator for the priority setting of seismic mitigation alternatives. The RMIR is a quantitative indicator that evaluates each alternative’s cost-effectiveness in terms of risk expectancy mitigation. Following the alternative’s RMIR value, it is possible to prioritize the alternatives meeting budget and time constraints. This paper presents the implementation of the proposed methodology through a case study of a generic oil pumping station. The case study includes twelve mitigation alternatives examined and evaluated according to the RMIR indicator.

Water is a valuable natural resource and essential for human life, so protecting critical water infrastructure is vital. Through directives such as the Network and Information Security Directive (NIS2), the European Union has made it mandatory to ensure that all critical infrastructure is adequately protected. Security measures taken to protect critical infrastructure are often limited to a national scope. The ECHO Early Warning System (E-EWS) is a tool that enables communication and cooperation across national borders. It focuses on a warning system that allows people to know almost immediately what is happening, to react appropriately and to disseminate this information to trusted partners. With geopolitical tensions and cyberattacks on the rise, this work in progress employs a literature review and case analysis to identify similarities between recent cyberattacks on critical water infrastructure and to determine what E-EWS could have done in these instances. The results show that key similarities correlate with current events: political threat actors, slow detection, fear as a weapon, information silos and people as weak links. With the E-EWS, threats are detected almost immediately, allowing mitigation actions to begin much earlier. By sharing information, knowledge grows, connecting and strengthening the overall security of E-EWS users. Attackers do not care about borders, so the cybersecurity of critical water infrastructure is no longer limited to national borders. International cooperation would help reduce the burden caused by some countries’ own resource constraints. Based on these results, the E-EWS plays a key role in the future protection of EU critical water infrastructure.

Background: Traditional cybersecurity approaches, such as firewalls, intrusion detection systems, and antivirus software, are increasingly inadequate in countering sophisticated attacks that exploit emerging vulnerabilities in supply chains, industrial control systems (ICS), and operational technologies. Aim: This review deals with challenges and innovations concerning the enhancement of cybersecurity measures taken for critical infrastructures, with a focus on energy grids, healthcare systems, and transportation networks. The study aims at identification of vulnerabilities, an assessment of advanced threat detection systems, and analysis of network protection protocols for improvements in resilience against cyber threats. Study Design: The study is a peer literature review from 2019 to 2024 concerning cybersecurity measures in critical infrastructures. The result will therefore, involve a selection from various scholarly journals in an informed approach. Methodology: The research uses a peer literature review methodology. The databases employed in this paper are Google Scholar, Scopus, IEEE Xplore, and the International Journal of Critical Infrastructure Protection. Articles were selected based on relevance to cybersecurity in critical infrastructure, focusing on advanced threat detection, network protection, and resilience strategies. Results: The review identifies 25 key studies that show a growth in sophistication in cyber threats against critical infrastructure. Among the promising technologies to mitigate the risks are AI-driven threat detection, blockchain for secure data transmission, and zero-trust architectures. Case studies from the energy and healthcare sectors demonstrate how these technologies can enhance resilience. Yet, resource constraints, lack of standardized protocols, and human error remain significant barriers. Conclusions: The study concludes that though there has been significant development in the cybersecurity measures of critical infrastructure, continuous innovation and collaboration by all stakeholders are required to overcome the challenges faced. Future research should be directed towards the development of standardized frameworks, better workforce training, and the long-term efficacy of emerging technologies. By addressing these areas, the study underscores the practical importance of advancing cybersecurity measures to safeguard critical infrastructure in energy, healthcare, and transportation sectors.

Building energy retrofits can reduce emissions and increase cost savings. Some retrofits that can deliver higher emissions savings are not popular due to a lack of economic justifications. Financial incentives can be used to change buyer perception around such retrofits. This study proposes a framework to identify the best-performing retrofit strategies for a given building cluster and the optimal incentive amounts to promote the chosen strategies, accounting for uncertainties, stakeholder priorities, and budget constraints. The proposed framework was demonstrated using a case study complemented with policy insights. Life cycle cost savings and capital cost significantly impact retrofit purchase decisions. Case study results showed that retrofitting houses heated with electricity can produce significant cost savings. However, adopting energy-conscious behaviours in houses heated with natural gas and injecting renewable natural gas into the gas supply can produce two times more emissions savings achieved by any retrofit strategy applied to an electrically heated house. This indicates the need for adopting performance-based incentives over the prescriptive approach to reward occupant efforts in addition to asset performance. Despite potential life cycle cost savings, incentives must be complemented with low-interest loans to promote retrofit strategies carrying higher capital costs.

Multi-period sustainable and integrated recycling network for municipal solid waste – A case study in Tehran

Competitive Influence Maximization ( CIM ) problem, which seeks a seed set nodes of a player or a company to propagate their product’s information while at the same time their competitors are conducting similar strategies, has been paid much attention recently due to its application in viral marketing. However, existing works neglect the fact that the limited budget and time constraints can play an important role in competitive influence strategy of each company. In addition, based on the the assumption that one of the competitors dominates in the competitive influence process, the majority of prior studies indicate that the competitive influence function (objective function) is monotone and submodular.This led to the fact that CIM can be approximated within a factor of 1 − 1 / e − ϵ by a Greedy algorithm combined with Monte Carlo simulation method. Unfortunately, in a more realistic scenario where there is fair competition among competitors, the objective function is no longer submodular. In this paper, we study a general case of CIM problem, named Budgeted Competitive Influence Maximization ( BCIM ) problem, which considers CIM with budget and time constraints under condition of fair competition. We found that the objective function is neither submodular nor suppermodular. Therefore, it cannot admit Greedy algorithm with approximation ratio of 1 − 1 / e . We propose Sandwich Approximation based on Polling-Based Approximation ( SPBA ), an approximation algorithm based on Sandwich framework and polling-based method. Our experiments on real social network datasets showed the effectiveness and scalability of our algorithm that outperformed other state-of-the-art methods. Specifically, our algorithm is scalable with million-scale networks in only 1.5 min.

Coastal communities are increasingly vulnerable to hurricanes, which cause billions of dollars in damage annually through wind, storm surge, and flooding. Mitigation efforts are essential to reduce these impacts but face significant challenges, including uncertainties in hazard prediction, damage estimation, and recovery costs. Resource constraints and the disproportionate burden borne by socioeconomically vulnerable groups further complicate retrofitting strategies. This study presents a probabilistic methodology to assess and mitigate hurricane risks by integrating hazard analysis, building fragility, and economic loss assessment. The methodology prioritizes retrofitting strategies using a risk‐informed, equity‐focused approach. Multi‐objective optimization balances cost‐effectiveness and risk reduction while promoting fair resource allocation among socioeconomic groups. The novelty of this study lies in its direct integration of equity as an objective in resource allocation through multi‐objective optimization, its comprehensive consideration of multi‐hazard risks, its inclusion of both direct and indirect losses in cost assessments, and its use of probabilistic hazard analysis to incorporate varying time horizons. A case study of the Galveston testbed demonstrates the methodology's potential to minimize damage and foster equitable resilience. Analysis of budget scenarios and trade‐offs between cost and equity underscores the importance of comprehensive loss assessments and equity considerations in mitigation and resilience planning. Key findings highlight the varied effectiveness of retrofitting strategies across different budgets and time horizons, the necessity of addressing both direct and indirect losses, and the importance of multi‐hazard considerations for accurate risk assessments. Multi‐objective optimization underscores that equitable solutions are achievable even under constrained budgets. Beyond a certain point, achieving equity does not necessarily increase expected losses, demonstrating that more equitable solutions can be implemented without compromising overall cost‐effectiveness.

Critical infrastructure doubling as social infrastructure has been a useful strategy for centuries. Projects with these overlapping programs usually spring from a handful of different design scenarios. They are often built initially as hard infrastructure and converted to social infrastructure at the end of their useful life. They can be modifications of existing ‘still-in-use’ critical infrastructure projects. Lastly, they can be designed as overlapping critical and social infrastructure from their conception.One method for establishing critical/social infrastructure is through enhanced public works projects where hard infrastructure is injected with additional social program. Often, this “thickening” of the program can face uphill battles related to increased funding, red tape, or public backlash, however, commoning, (the grass roots collaborative effort of a community to meet its needs), can be a viable alternative method for the creation of these enhancements. There already exist precedents of critical/social infrastructure evolving out of the commons. Chicano Park in San Diego and FDR Skate Park in Philadelphia are lasting examples which are related to residual space left after interstate highways were built. This paper will present ongoing research and teaching related to the overlap of critical and social infrastructure specifically as it relates to atypical methods for their creation. It will present a design course that explores opportunities to create social infrastructure in the overlooked spaces left by the construction of critical infrastructure. It will discuss this on a global level through case studies from around the world and a local level from a series of student design projects situated in a mid-size southern U.S. city. In these projects, residual spaces, (the highway right-of-way and surrounding neighborhood), become the setting for projects that can tap into the commons and be re-imagined as social infrastructure.

The purpose of this article is to study the theoretical foundations of the concept of fiscal decentralization, as the main path of self-development of the national economy of any country, and to develop mathematical tools that support decision-making in the aspect of “hard” budget constraints. The study of the problems of fiscal policy formation in foreign countries presented in modern scientific literature has revealed that the degree of application of the concepts of “soft” and “hard” budget restrictions is an actual topic in the theory of fiscal federalism. It has been substantiated that decision-making within the framework of “soft” budget constraints (financial assistance) leads to low tax autonomy of territories and limited liability of regional and municipal authorities for the results of their financial policy. As a research hypothesis, we put forward the thesis that it is necessary to create conditions for encouraging subnational authorities to support the territorial economy by granting them the possibility to use part of the taxes collected in the respective territories. The implementation of this thesis has given rise to the problem of quantifying decisions made regarding the establishment of standards for the distribution of tax revenues between budgets of different levels of the hierarchy of the country’s budget system. In terms of solving this problem, the author has constructed mathematical models based on the use of synthesis of mathematical apparatus of the theory of stochastic automata, fuzzy algebra, and simulation. In terms of solving this problem, the author proposed the use of mathematical modeling methods. The article presents the results of constructing economic and mathematical models to support decision-making in the vertical distribution of tax revenues between budgets. The models include stochastic automata, as mathematical abstractions, describing the expedient behavior of an economic agent when choosing management alternatives for territories of different levels of economic development. The transition functions of automaton models are formally described on the basis of the synthesis of mathematical apparatus of the theories of stochastic automata operating in random environments and fuzzy sets. The expediency property of the behavior of automaton models is justified by proving the corresponding theorems. The random environment in which stochastic automata are immersed is formed by a simulation model. The article demonstrates the results of experiments carried out on models, as well as a conceptual scheme of interaction between the automaton and simulation models.

Critical infrastructures and associated real time Informational systems need some security protection mechanisms that will be able to detect and respond to possible attacks. For this reason, Anomaly Detection Systems (ADS), as part of a Security Information and Event Management (SIEM) system, are needed for constantly monitoring and identifying potential threats inside an Information Technology (IT) system. Typically, ADS collect information from various sources within a CI system using security sensors or agents and correlate that information so as to identify anomaly events. Such sensors though in a CI setting (factories, power plants, remote locations) may be placed in open areas and left unattended, thus becoming targets themselves of security attacks. They can be tampering and malicious manipulated so that they provide false data that may lead an ADS or SIEM system to falsely comprehend the CI current security status. In this paper, we describe existing approaches on security monitoring in critical infrastructures and focus on how to collect security sensor–agent information in a secure and trusted way. We then introduce the concept of hardware assisted security sensor information collection that improves the level of trust (by hardware means) and also increases the responsiveness of the sensor. Thus, we propose a Hardware Security Token (HST) that when connected to a CI host, it acts as a secure anchor for security agent information collection. We describe the HST functionality, its association with a host device, its expected role and its log monitoring mechanism. We also provide information on how security can be established between the host device and the HST. Then, we introduce and describe the necessary host components that need to be established in order to guarantee a high security level and correct HST functionality. We also provide a realization–implementation of the HST overall concept in a FPGA SoC evaluation board and describe how the HST implementation can be controlled. In addition, in the paper, two case studies where the HST has been used in practice and its functionality have been validated (one case study on a real critical infrastructure test site and another where a critical industrial infrastructure was emulated in our lab) are described. Finally, results taken from these two case studies are presented, showing actual measurements for the in-field HST usage.

This study examines the effect of corrosion on reinforced concrete structural elements of a bridge overpass in seismic affected areas. Starting from a literature review to identify the existing deteriorating models, a case study is selected to perform seismic analyses. It allows to assess the structural response at different levels of reinforced concrete degradation due to corrosion. The selected case study is a frequently used structural system with several existing examples in critical infrastructures all around the world. Consequently, an in-depth analysis of the degradation of this type of system, with the identification of the most appropriate time for restoration and the possible retrofitting strategies may be of interest. The bridge is assumed to be located in Sicily, the largest island in Southern Italy. In particular, a site close to the Strait of Messina has been selected with a high seismic hazard. According to the current Italian standard for constructions, it belongs to the first seismic category among four. Indeed, a strong earthquake destroyed all the city in 1908. A finite element model of the bridge overpass is prepared to perform the seismic analyses. Different levels of degradation have been simulated by using a deterministic approach. They include the reduction of the steel reinforcement areas, the bond decreasing and the steel strength losses due to corrosion. The position of the bridge concerning the sea is also considered because it can also affect the steel reinforcement degradation due to pitting corrosion. Finally, retrofitting strategies to improve the seismic performance of the bridge are evaluated to preserve it from demolishing and rebuilding.

Critical infrastructure (CI) is of vital importance to national economy and social stability. Although the rapid development of information technology improves the system performance of CI, it also makes CI more vulnerable to cyber attackers. However, due to the CI characteristics which include complex cyber-physical interaction and the interdependence in physical network, the cybersecurity protection methods of ITs cannot be used in CI directly. This paper provides a dynamic decision-making approach about cybersecurity protection for CI based on risk reduction. Firstly, a dynamic risk assessment is presented for CI after the attack-defense strategy is executed. Then, the optimal defense strategies are chosen in each station in CI, with considering the resource constraints. Finally, several simulations are carried out on a water-supply system. The simulation results demonstrate the effectiveness of the proposed approach.

The increasing use of 5 G networks in core sectors necessitates its adequacy in terms of security. This paper presents a new mathematical model that bolsters cybersecurity in critical infrastructures based on 5 G technology. This framework incorporates the Moving Target Defence (MTD) method with a dynamic game theory model to respond to the fact that cyber threats are not static when a critical infrastructure has 5 G facility. The new game-theoretic concept enhances defense processes against cyber threats targeted on mobile networks in critical infrastructure. It has been developed for a game of incomplete information with two players- an attacker and a defender, where both have resource constraints and MTD. The suggested model is tested via various simulations and benchmarked against traditional static defense methods. Results demonstrate significant improvements across multiple metrics: a 23% boost in the network reliability, a 17.1% drop in the false positives ratios and a 24.1% improvement in resource utilization. This work benefits the field as it provides insight into how game theoretical methods can be applied when addressing the security issues of a 5 G-supported utility infrastructure environment to ensure a safer, more secure and much more reliable world in the future.