iOSDBuilder: Uma Ferramenta de Construção de Datasets para Detecção de Malwares iOS

• João Guilherme Freitas UFAM
• Vanderson Rocha UFAM
• Eduardo Feitosa UFAM

DOI: https://doi.org/10.5753/sbseg_estendido.2023.234987

Abstract

The lack of datasets to train and test solutions for identifying and classifying malicious applications in the iOS operating system is a reality. While on the Android platform, there are dozens, there is no public dataset to facilitate the training and testing of detection solutions. To solve this problem, iOSDBuilder was developed to build datasets capable of analyzing and detecting iOS malware. iOSDBuilder is separated into four independent modules with different features and tools for building up-to-date datasets. As a result, it was possible to generate a dataset with 176 applications, of which 9 were classified as possibly malicious by the VirusTotal scanners.

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