Network overload due to massive attacks

Kornbluth, Yosef; Barach, Gilad; Tuchman, Yaakov; Kadish, Benjamin; Cwilich, Gabriel; Buldyrev, Sergey V.

doi:10.1103/physreve.97.052309

Cited by 26 publications

(22 citation statements)

References 30 publications

(26 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the sizes of blackouts are much smaller in the USWI with a realistic design than in an artificial DADA model with a different spatial organization. In particular, we study the dependence of the blackout size and the dynamics of the cascading failures on a set of three parameters that characterize the robustness of the grid: (1) tolerance α, the ratio of the maximum flow a line can carry to its initial load (Kornbluth et al, 2018;Motter & Lai, 2002;Motter, 2004); (2) the minimum flow I p which any line in the network can carry independent of its initial load; and (3) the amount of flow in the initial failed line compared to the distribution of the flows in the grid (I u ). We characterize I p and I u by dimensionless parameters p (called the level of protection) and u (called the significance of initial failure).…”

Section: Introductionmentioning

confidence: 99%

A study of cascading failures in real and synthetic power grid topologies

Spiewak¹,

Soltan²,

Forman³

et al. 2018

Net Sci

Self Cite

View full text Add to dashboard Cite

Using the linearized DC power flow model, we study cascading failures and their spatial and temporal properties in the US Western Interconnect (USWI) power grid. We also introduce the preferential Degree And Distance Attachment (DADA) model, with similar degree distributions, resistances, and currents to the USWI. We investigate the behavior of both grids resulting from the failure of a single line. We find that the DADA model and the USWI model react very similarly to that failure, and that their blackout characteristics resemble each other. In many cases, the failure of a single line can cause cascading failures, which impact the entire grid. We characterize the resilience of the grid by three parameters, the most important of which is tolerance α, which is the ratio of the maximal load a line can carry to its initial load. We characterize a blackout by its yield, which we define as the ratio of the final to the initial consumed currents. We find that if α ≥ 2, the probability of a large blackout occurring is very small. By contrast, in a broad range of 1 < α < 2, the initial failure of a single line can result, with a high probability, in cascading failures leading to a massive blackout with final yield less than 80%. The yield has a bimodal distribution typical of a first-order transition, i.e., the failure of a randomly selected line leads either to an insignificant current reduction or to a major blackout. We find that there is a latent period in the development of major blackouts during which few lines are overloaded, and the yield remains high.The duration of this latent period is proportional to the tolerance. The existence of the latent period suggests that intervention during early time steps of a cascade can significantly reduce the risk of a major blackout.

show abstract

Section: Introductionmentioning

confidence: 99%

A study of cascading failures in real and synthetic power grid topologies

Spiewak¹,

Soltan²,

Forman³

et al. 2018

Net Sci

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recently, the model of Ref. [89] has been explored for a case when a macroscopic fraction 1 − p of nodes fails at the initial condition [67], as opposed to one node in the original model [89]. In this case, the order parameter can be taken either as the fraction of survived nodes, or as the fraction of nodes in the giant component (GC).…”

Section: Cascade Of Failures In Single Complex Networkmentioning

confidence: 99%

Cascading failures in complex networks

Valdez

Shekhtman

Rocca

et al. 2020

Journal of Complex Networks

View full text Add to dashboard Cite

Cascading failure is a potentially devastating process that spreads on real-world complex networks and can impact the integrity of wide-ranging infrastructures, natural systems and societal cohesiveness. One of the essential features that create complex network vulnerability to failure propagation is the dependency among their components, exposing entire systems to significant risks from destabilizing hazards such as human attacks, natural disasters or internal breakdowns. Developing realistic models for cascading failures as well as strategies to halt and mitigate the failure propagation can point to new approaches to restoring and strengthening real-world networks. In this review, we summarize recent progress on models developed based on physics and complex network science to understand the mechanisms, dynamics and overall impact of cascading failures. We present models for cascading failures in single networks and interdependent networks and explain how different dynamic propagation mechanisms can lead to an abrupt collapse and a rich dynamic behaviour. Finally, we close the review with novel emerging strategies for containing cascades of failures and discuss open questions that remain to be addressed.

show abstract

“…If we think of infrastructures such as power grids, road networks or the Internet, it is reasonable to conceive heavy loaded nodes as the most prone to failure, so RB-like damages are possible not only as a targeted attack but as a failure. Other authors have studied the vulnerability of these systems in terms of cascading failures using as a proxy for the loads the betweenness of the nodes [12,22]. From a novel perspective, our work adds more evidence to point out that many systems-in which our modern life relies on-may seem robust but hinder critical vulnerabilities.…”

Section: Discussionmentioning

confidence: 89%

Scaling of percolation transitions on Erdös-Rényi networks under centrality-based attacks

2020

View full text Add to dashboard Cite

The study of network robustness focuses on the way the overall functionality of a network is affected as some of its constituent parts fail. Failures can occur at random or be part of an intentional attack and, in general, networks behave differently against different removal strategies. Although much effort has been put on this topic, there is no unified framework to study the problem. Whilst random failures have been mostly studied under percolation theory, targeted attacks have been recently restated in terms of network dismantling. In this work, we link these two approaches by performing a finite-size scaling analysis to four dismantling strategies over Erdös-Rényi networks: initial and recalculated high degree removal (ID and RD) and initial and recalculated high betweenness removal (IB and RB). We find that both degree-based attacks lie into the same universality class, but the betweenness-based attacks differ significantly. In particular, RB produces a very abrupt transition with a hump in the cluster size distribution near the critical point, resembling some explosive percolation processes. *

show abstract

Network overload due to massive attacks

Cited by 26 publications

References 30 publications

A study of cascading failures in real and synthetic power grid topologies

A study of cascading failures in real and synthetic power grid topologies

Cascading failures in complex networks

Scaling of percolation transitions on Erdös-Rényi networks under centrality-based attacks

Contact Info

Product

Resources

About