Network Resilience is Key to Surviving Compound Hazard Events

“Cyberattacks are almost continuously happening,” Ganguly noted. “Sometimes it is nation states, sometimes it is rogue agencies, sometimes it is just a few bad actors. And weather extremes have been growing in frequency and duration. So, the chance that they will be concurrent at some point is high.”

The researchers use computer simulations to model such compound threat events directed toward networks-of-networks to begin to understand how failures cascade through these interconnected systems. The insights gained inform design and engineering recommendations on how to make interconnected networks more resilient to natural and human threats and be primed to recover efficiently.

Old Network, New Problems
Real-world networks-of-networks such as the London Rail Network are constrained by geography and were originally designed for efficiency. For instance, some rail stations are located near major waterways to facilitate the transfer of people and cargo from ships to rail.

“By doing multiple simulations on this network-of-networks, you find that some of the design principles that were used back in the older days like having your prominent stations near the river may make the system vulnerable to failure,” said Nishant Yadav, a graduate student in Ganguly’s sustainability and data sciences laboratory at Northeastern University.

That vulnerability exists because the stations near rivers are more likely to flood during extreme weather events. If these major network nodes are shut early in a disaster, the impacts will cascade through the system, added Yadav, who led the research on the London Rail Network while an intern with Chatterjee at PNNL.

Yadav is the lead author of a paper on the team’s findings published in the Nature research journal Scientific Reports.

Compound Extremes
The team also ran multiple simulations to understand how the London Rail Network would respond to compound extremes such as a flooding event that is immediately followed by a cyberattack timed to inflict maximum damage to an already compromised network-of-networks.

The simulations showed that compound disruptions do cause network-wide failure, but the impact is not disproportionate as hypothesized, at least on the London Rail Network.

“One happens over and above the other, and the cyber dominates a lot,” Ganguly said. “The assumption that we make here is that the adversary, the cyber attacker, has ample knowledge about the system and if the cyber attacker has a lot of knowledge, they can cause significant damage and that damage might dominate over other damages, although these other damages might be more continuous.”

Well-Grounded Principles
Finally, the team sought to quantify the value of applying network science principles to the recovery of systems such as the London Rail Network in the wake of a compound failure.

Typically, the researchers explained, engineers use computationally intense calculations to determine the most optimum next step to bring a failed network back online. The researchers compared that approach to a well-grounded network science principle that prioritizes recovery of the most central nodes.

The network science approach, according to the simulations, outperformed the more computationally expensive approach.

“These network science principles will hold value not just for calculating the robustness of these systems, but they can also guide the practitioner in rapidly generating feasible recovery profiles,” Yadav said.

Real-World Applications
Going forward, the researchers aim to apply the insights from this research to the development of computational frameworks to inform the design and engineering of resilient networks.

For example, the team is set to launch a multi-year U.S. Department of Defense (DoD) project called Network Infrastructures under Compound Extremes, or NICE, to develop theoretical frameworks to make DoD installations resilient to compound extremes, such as the dual threats of extreme weather and cyberattacks.

The ongoing research, said Chatterjee, “is translating network science theory into practice with real world engineering principles while taking into account policy driven perspective and directives.”