Evaluating Graph Vulnerability and Robustness using TIGER

• URL: http://arxiv.org/abs/2006.05648v2
• Date: Sun, 15 Aug 2021 19:37:38 GMT
• Title: Evaluating Graph Vulnerability and Robustness using TIGER
• Authors: Scott Freitas, Diyi Yang, Srijan Kumar, Hanghang Tong, Duen Horng Chau
• Abstract summary: TIGER is an open-sourced Python toolbox to study network robustness. TIGER contains 22 robustness graph measures with both original and fast approximate versions. TIGER has been integrated into the Nvidia Data Science Teaching Kit available to educators across the world; and Georgia Tech's Data and Visual Analytics class with over 1,000 students.
• Score: 77.50446320230624
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Network robustness plays a crucial role in our understanding of complex interconnected systems such as transportation, communication, and computer networks. While significant research has been conducted in the area of network robustness, 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 has been integrated into the Nvidia Data Science Teaching Kit available to educators across the world; and Georgia Tech's Data and Visual Analytics class with over 1,000 students. TIGER is open sourced at: https://github.com/safreita1/TIGER

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