arXiv subjects

Igor Linkov

Publications and source records attributed to Igor Linkov.

28 records · Page 2Linked to original sources

arXiv2020

The Need to Reconcile Concepts that Characterize Systems Withstanding Threats

Desirable system performance in the face of threats and disruptions has been characterized by various management concepts. Through semi-structured interviews with editors of journals in the fields of emergency response and systems management, a literature review, and professional judgment, we identified nine related and often interchangeably-used system performance concepts: adaptability, agility, reliability, resilience, resistance, robustness, safety, security, and sustainability. We analysed expert responses and reviewed the linguistic definitions and mathematical framing of these concepts to understand their applications. We found a lack of consensus on their usage between interview subjects, but using a mathematical framing enriched the linguistic definitions and enabled formulating comparative visualizations and system-specific definitions for the concepts. We propose a conceptual framing to relate the concepts for management purposes. A better understanding of these concepts will allow system planners to pursue management strategies best suited to their unique system dynamics and specific objectives of 'goodness' that all these concepts bring.

physics.soc-ph↗

arXiv2019

Lack of Resilience in Transportation Networks: Economic Implications

Disruptions to transportation networks are inevitable. Currently, most mandated development-related transportation planning is intended to prepare for frequently occurring and observable disruptions while low probability events that have not yet materialized attract less attention. When road networks are not resilient, these unpredictable events can cause significant delays that may not be proportional to the extent of the disruption. Enhancing resilience can help in mitigating consequences of disruptions but requires financial investment that is difficult to justify given that low probability event may not have materialized. This paper highlights economic implications of unmitigated random disruptions in urban road systems and makes the case for investment in transportation network resilience. We utilized a model of urban transportation network performance that quantifies resilience and demonstrated its integration with microeconomic transportation planning model REMI TranSight. The model was applied to 10 cities in the USA to calculate several economic indicators under baseline scenario where economic impact was assumed to be proportional to the magnitude of disruptive events and under a test scenario where the magnitude of disruption was used to calculate additional delays in transportation networks and these additional delays were explicitly integrated in REMI model. Results show that GDP losses suffered as a result of disruption may be far more significant in the case scenario and economic output is not necessarily back to normal in the year the following disruptive event. We thus conclude that support for investment decisions on network efficiency and resilience management should be based on a framework that utilizes resilience, quantified in terms that are compatible with standard practice, and scenarios to test the implications of topological attributes.

physics.soc-ph↗

arXiv2018

Fundamental Concepts of Cyber Resilience: Introduction and Overview

Given the rapid evolution of threats to cyber systems, new management approaches are needed that address risk across all interdependent domains (i.e., physical, information, cognitive, and social) of cyber systems. Further, the traditional approach of hardening of cyber systems against identified threats has proven to be impossible. Therefore, in the same way that biological systems develop immunity as a way to respond to infections and other attacks, so too must cyber systems adapt to ever-changing threats that continue to attack vital system functions, and to bounce back from the effects of the attacks. Here, we explain the basic concepts of resilience in the context of systems, discuss related properties, and make business case of cyber resilience. We also offer a brief summary of ways to assess cyber resilience of a system, and approaches to improving cyber resilience.

cs.CR↗

arXiv2018

Approaches to Enhancing Cyber Resilience: Report of the North Atlantic Treaty Organization (NATO) Workshop IST-153

This report summarizes the discussions and findings of the 2017 North Atlantic Treaty Organization (NATO) Workshop, IST-153, on Cyber Resilience, held in Munich, Germany, on 23-25 October 2017, at the University of Bundeswehr. Despite continual progress in managing risks in the cyber domain, anticipation and prevention of all possible attacks and malfunctions are not feasible for the current or future systems comprising the cyber infrastructure. Therefore, interest in cyber resilience (as opposed to merely risk-based approaches) is increasing rapidly, in literature and in practice. Unlike concepts of risk or robustness - which are often and incorrectly conflated with resilience - resiliency refers to the system's ability to recover or regenerate its performance to a sufficient level after an unexpected impact produces a degradation of its performance. The exact relation among resilience, risk, and robustness has not been well articulated technically. The presentations and discussions at the workshop yielded this report. It focuses on the following topics that the participants of the workshop saw as particularly important: fundamental properties of cyber resilience; approaches to measuring and modeling cyber resilience; mission modeling for cyber resilience; systems engineering for cyber resilience, and dynamic defense as a path toward cyber resilience.

cs.CR↗

arXiv2018

Stability of a Giant Connected Component in a Complex Network

We analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network consists of the same nodes, regardless of the specific set of deactivated links. Our results are intuitive in the case of single-layered systems: the presence of large degree nodes in a single-layered network ensures both its robustness and stability. In contrast, we find that interdependent networks that are robust to adverse events have unstable connected components. Our results bring novel insights to the design of resilient network topologies and the reinforcement of existing networked systems.

physics.soc-ph↗

arXiv2018

Resilience management during large-scale epidemic outbreaks

Assessing and managing the impact of large-scale epidemics considering only the individual risk and severity of the disease is exceedingly difficult and could be extremely expensive. Economic consequences, infrastructure and service disruption, as well as the recovery speed, are just a few of the many dimensions along which to quantify the effect of an epidemic on society's fabric. Here, we extend the concept of resilience to characterize epidemics in structured populations, by defining the system-wide critical functionality that combines an individual's risk of getting the disease (disease attack rate) and the disruption to the system's functionality (human mobility deterioration). By studying both conceptual and data-driven models, we show that the integrated consideration of individual risks and societal disruptions under resilience assessment framework provides an insightful picture of how an epidemic might impact society. In particular, containment interventions intended for a straightforward reduction of the risk may have net negative impact on the system by slowing down the recovery of basic societal functions. The presented study operationalizes the resilience framework, providing a more nuanced and comprehensive approach for optimizing containment schemes and mitigation policies in the case of epidemic outbreaks.

physics.soc-ph↗

arXiv2017

Resilience and efficiency in transportation networks

Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that improve resilience (defined as system recovery from additional disruptions) is still scarce. In this effort, we represent paved roads as a transportation network by mapping intersections to nodes and road segments between the intersections to links. We built road networks for 40 of the urban areas defined by the U.S. Census Bureau. We developed and calibrated a model to evaluate traffic delays using link loads. The loads may be regarded as traffic-based centrality measures, estimating the number of individuals using corresponding road segments. Efficiency was estimated as the average annual delay per peak-period auto commuter, and modeled results were found to be close to observed data, with the notable exception of New York City. Resilience was estimated as the change in efficiency resulting from roadway disruptions and was found to vary between cities, with increased delays due to a 5% random loss of road linkages ranging from 9.5% in Los Angeles to 56.0% in San Francisco. The results demonstrate that many urban road systems that operate inefficiently under normal conditions are nevertheless resilient to disruption, whereas some more efficient cities are more fragile. The implication is that resilience, not just efficiency, should be considered explicitly in roadway project selection and justify investment opportunities related to disaster and other disruptions.

physics.soc-ph↗

arXiv2015

Security Metrics in Industrial Control Systems

Risk is the best known and perhaps the best studied example within a much broader class of cyber security metrics. However, risk is not the only possible cyber security metric. Other metrics such as resilience can exist and could be potentially very valuable to defenders of ICS systems. Often, metrics are defined as measurable properties of a system that quantify the degree to which objectives of the system are achieved. Metrics can provide cyber defenders of an ICS with critical insights regarding the system. Metrics are generally acquired by analyzing relevant attributes of that system. In terms of cyber security metrics, ICSs tend to have unique features: in many cases, these systems are older technologies that were designed for functionality rather than security. They are also extremely diverse systems that have different requirements and objectives. Therefore, metrics for ICSs must be tailored to a diverse group of systems with many features and perform many different functions. In this chapter, we first outline the general theory of performance metrics, and highlight examples from the cyber security domain and ICS in particular. We then focus on a particular example of a class of metrics that is different from the one we have considered in earlier chapters. Instead of risk, here we consider metrics of resilience. Resilience is defined by the National Academy of Sciences (2012) as the ability to prepare and plan for, absorb, recover from, or more successfully adapt to actual or potential adverse events. This chapter presents two approaches for the generation of metrics based on the concept of resilience using a matrix-based approach and a network-based approach. Finally, a discussion of the benefits and drawbacks of different methods is presented along with a process and tips intended to aid in devising effective metrics.

cs.CR↗

arXiv2015

Operational resilience: concepts, design and analysis

Building resilience into today's complex infrastructures is critical to the daily functioning of society and its ability to withstand and recover from natural disasters, epidemics, and cyber-threats. This study proposes quantitative measures that implement the definition of engineering resilience advanced by the National Academy of Sciences. The approach is applicable across physical, information, and social domains. It evaluates the critical functionality, defined as a performance function of time set by the stakeholders. Critical functionality is a source of valuable information, such as the integrated system resilience over a time interval, and its robustness. The paper demonstrates the formulation on two classes of models: 1) multi-level directed acyclic graphs, and 2) interdependent coupled networks. For both models synthetic case studies are used to explore trends. For the first class, the approach is also applied to the Linux operating system. Results indicate that desired resilience and robustness levels are achievable by trading off different design parameters, such as redundancy, node recovery time, and backup supply available. The nonlinear relationship between network parameters and resilience levels confirms the utility of the proposed approach, which is of benefit to analysts and designers of complex systems and networks.

physics.soc-ph↗

arXiv2013

Power-law of Aggregate-size Spectra in Natural Systems

Patterns of animate and inanimate systems show remarkable similarities in their aggregation. One similarity is the double-Pareto distribution of the aggregate-size of system components. Different models have been developed to predict aggregates of system components. However, not many models have been developed to describe probabilistically the aggregate-size distribution of any system regardless of the intrinsic and extrinsic drivers of the aggregation process. Here we consider natural animate systems, from one of the greatest mammals - the African elephant (\textit{Loxodonta africana}) - to the \textit{Escherichia coli} bacteria, and natural inanimate systems in river basins. Considering aggregates as islands and their perimeter as a curve mirroring the sculpting network of the system, the probability of exceedence of the drainage area, and the Hack's law are shown to be the the Korčak's law and the perimeter-area relationship for river basins. The perimeter-area relationship, and the probability of exceedence of the aggregate-size provide a meaningful estimate of the same fractal dimension. Systems aggregate because of the influence exerted by a physical or processes network within the system domain. The aggregate-size distribution is accurately derived using the null-method of box-counting on the occurrences of system components. The importance of the aggregate-size spectrum relies on its ability to reveal system form, function, and dynamics also as a function of other coupled systems. Variations of the fractal dimension and of the aggregate-size distribution are related to changes of systems that are meaningful to monitor because potentially critical for these systems.

q-bio.QM↗