Evaluating Graph Vulnerability and Robustness using TIGER

06/10/2020
by   Scott Freitas, et al.
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The study of network robustness is a critical tool in the characterization and understanding of complex interconnected systems such as transportation, infrastructure, communication, and computer networks. Through analyzing and understanding the robustness of these networks we can:(1) quantify network vulnerability and robustness,(2) augment a network's structure to resist attacks and recover from failure, and (3) control the dissemination of entities on the network (e.g., viruses, propaganda). While significant research has been conducted on all of these tasks, no comprehensive open-source toolbox currently exists to assist researchers and practitioners in this important topic. This lack of available tools hinders reproducibility and examination of existing work, development of new research, and dissemination of new ideas. We contribute TIGER, an open-sourced Python toolbox to address these challenges. TIGER contains 22 graph robustness measures with both original and fast approximate versions; 17 failure and attack strategies; 15 heuristic and optimization based defense techniques; and 4 simulation tools. By democratizing the tools required to study network robustness, our goal is to assist researchers and practitioners in analyzing their own networks; and facilitate the development of new research in the field. TIGER is open-sourced at: https://github.com/safreita1/TIGER

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