Benchmarking Android malware analysis tools

Abstract

Abstract Today, malware is arguably one of the biggest challenges organizations face from a cybersecurity standpoint, regardless of the types of devices used in the organization. One of the most malware-attacked mobile operating systems today is Android. In response to this threat, this paper presents research on the functionalities and performance of different malicious Android application package analysis tools including one that uses machine learning techniques. In addition, it investigates how the use of these tools streamlines the process of detection, classification, and analysis of malicious APKs for Android operating system devices. The tools, that use Artificial Intelligence techniques, are more efficient than other current tools that do not use them. In this way, new approaches can be suggested in the specification, design, and development of new tools that help to analyze, from a cybersecurity point of view, the code of applications developed for this environment.