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Poster communications

GraphletMatchMaker: Visual Analytics Approaches to Graph Matching in Cybersecurity Communities

Natkamon Tovanich 1, 2 Alexis Pister 2 Gaëlle Richer 2 Paola Valdivia 2 Jean-Daniel Fekete 2 Christophe Prieur 3, 4 Petra Isenberg 2
2 AVIZ - Analysis and Visualization
Inria Saclay - Ile de France, LRI - Laboratoire de Recherche en Informatique
4 SID - Sociologie Information-Communication Design
I3, une unité mixte de recherche CNRS (UMR 9217) - Institut interdisciplinaire de l’innovation
Abstract : We report on our approach, statistical and graphical analysis, as well as three visual analytics tools we built to address the VAST 2020 Mini-Challenge 1. First, we compared the structure of subgraphs using node-link diagrams, graphlet frequencies, and temporal profiles. Second, we devised a method to extract a subgraph of the large graph that matches the identified graph structure and built a custom visu-alization to check our results. Finally, we developed another visual analytics tool to facilitate manual search for pairing person nodes that helped us to solve the challenge. The full report and visualizations are available at https://graphletmatchmaker.github.io/.
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https://hal.archives-ouvertes.fr/hal-02986447
Contributor : Natkamon Tovanich <>
Submitted on : Tuesday, November 3, 2020 - 12:55:38 AM
Last modification on : Thursday, November 5, 2020 - 3:24:37 AM

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  • HAL Id : hal-02986447, version 1

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Natkamon Tovanich, Alexis Pister, Gaëlle Richer, Paola Valdivia, Jean-Daniel Fekete, et al.. GraphletMatchMaker: Visual Analytics Approaches to Graph Matching in Cybersecurity Communities. IEEE Visual Analytics Science and Technology, VAST Challenge, Oct 2020, Virtual Conference, United States. ⟨hal-02986447⟩

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