A cross-border community for researchers with openness, equality and inclusion

ABSTRACT LIBRARY

Conception of an Autonomous Dynamic Analysis System for Android Malwares

Publisher: IEEE

Authors: Boudrega Amel, Université Paris Cité Benzouaoua Selma, Université Paris Cité Ea Philippe, Université Paris CitéSalem Osman, Université Paris Cité Mehaoua Ahmed, Université Paris Cité

  • Favorite
  • Share:

Abstract:

This paper focuses on dynamic analysis for malware detection on Android. Initially, a literature review was conducted to understand both static and dynamic analysis approaches and their limitations, particularly highlighting the shortcomings of static analysis. The study demonstrates techniques for extracting various traces, such as system calls and network traffic, using dynamic analysis. The core of the study is the design of an automated system for the dynamic analysis of Android malware. This system automates the capture and analysis of APK traces using modules that monitor system calls, debug logs, and network traffic. It was found that relying on a single dynamic analysis module is insufficient, leading to false negatives, whereas combining data from all three modules enhances detection accuracy. Future directions include developing an intermediary using MQTT to reduce database load and improving the learning process for the three modules.

Keywords: Dynamic Analysis,Malware Detection,Android Security,Network Traffic Analysis,Machine Learning

Published in: 2024 Asian Conference on Communication and Networks (ASIANComNet)

Date of Publication: --

DOI: -

Publisher: IEEE