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Conference Papers Year : 2022

DaViz: Visualization for Android Malware Datasets

Abstract

With millions of Android malware samples available, researchers have a large amount of data to perform malware detection and classification, specially with the help of machine learning. Thus far, visualization tools focus on single samples or one-to-many comparison, but not a many-to-many approach. In order to exploit the quantity of data from various datasets to obtain meaningful information, we propose DaViz, a visualization tool for Android malware datasets. With the aid of multiple chart types and interactive sample filtering, users can explore different application datasets and compare them. This new tool allows to get a better understanding of the datasets at hand, and help to continue research by narrowing the samples to those of interest based on selected characteristics.
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Dates and versions

hal-03709062 , version 1 (29-06-2022)

Identifiers

  • HAL Id : hal-03709062 , version 1

Cite

Tomás Concepción Miranda, Jean-François Lalande, Valérie Viet Triem Tong, Pierre Wilke. DaViz: Visualization for Android Malware Datasets. RESSI 2022 - Rendez-Vous de la Recherche et de l'Enseignement de la Sécurité des Systèmes d'Information, May 2022, Chambon-sur-Lac, France. pp.1-3. ⟨hal-03709062⟩
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