Multiscale Networks with Stochastic Interactions: Resiliency and Recovery Optimization under Large-Scale Attacks
Abstract
The goal of the proposed research is to conceptually advance our understanding of massive sequential, or cascading, processes in complex network systems that are caused by large-scale attacks, and their impact on the network’s structure, stability, and security. Key features of such attacks that will be addressed in the course of the proposed project include simultaneous incapacitation of a large number of network components, highly uncertain and stochastic network state following the attack, cascading failures of interconnected systems, and other similar “domino effects.” The proposed theoretical models will allow us to develop new rigorous methodologies for modeling and analysis of sequential or cascading events in multiscale network systems under largescale attacks along with the corresponding approaches for optimal failure-resistant and robust network design and control based on advanced optimization techniques, such as semidefinite programming.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 04, 2018
- Source ID
- HDTRA11610054
Entities
People
- Pavlo Krokhmal
Organizations
- Defense Threat Reduction Agency
- University of Arizona