SBIR/STTR Research Award

Network Resilience to Cascading Failure

Award identifier 8aea2db8912487d2008714d259c2133ffef33b29c0e43082a091ac5e07086560Awarding agency Department of Commerce · National Institute of Standards and Technology

Award amount

$400,000

Program and phase

SBIR · Phase II

Award year

2023

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Award details

Awarding agency
Department of Commerce
Branch
National Institute of Standards and Technology
Recipient company
CRITICALITY SCIENCES INC
Proposal award date
2023-10-01
Contract end date
2025-09-30
UEI
zcevncspnxg4
Solicitation number
2023-NIST-SBIR-02
Topic code
6

Research abstract

The 21st century is the Age of the Network. Operators and clients of critical infrastructure networks are now vulnerable to cascading failures that they could not have seen coming. “Cascading” failure events remain a vital unsolved challenge as critical infrastructure network operators and regulators struggle to define and operationalize resilience, and measurement of interdependent network resilience to “all-hazards.” We must quickly translate the emerging theories of networked systems resilience into practicable methods that demonstrate cost-effective and measurable improvements in the risk all-hazards events pose to critical infrastructure networks. In work funded by a Phase I grant from the 2022 NIST SBIR program, Criticality Sciences demonstrated that the SCADA and power network interdependencies were the source of most of a midsize U.S. water distribution operator’s vulnerability to cascading failure events. With the support of our industry partner, Phase II will validate input data used by the NetResilience software. Results will translate the costs and benefits of mitigation into the preferred financial risk and decision metrics used by the operator, its public service commission, and its bond issuers. NetResilience will provide scalable, market-ready outputs for optimizing and financing investments to improve network resilience.

Technology keywords

Not reported

Agency intelligence

Department of Commerce

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