Evaluating Graph Vulnerability and Robustness using TIGER

TL;DR

TIGER is an open-source Python toolbox that provides comprehensive tools for analyzing network robustness, including measures, attack strategies, defenses, and simulations, to support research and education in complex network systems.

Contribution

The paper introduces TIGER, a new open-source toolbox with extensive robustness measures, attack and defense strategies, and simulation tools for network analysis.

Findings

TIGER includes 22 robustness measures and 17 attack strategies.

It has been integrated into educational platforms with over 1,000 students.

The toolbox enhances reproducibility and development in network robustness research.

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