TrojanDroid: Android Malware Detection for Trojan Discovery Using Convolutional Neural Networks

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNpeer-review

Abstract

Android platforms are widely used nowadays in different forms such as mobile phones and tablets, and this has made the Android platform an attractive target for hackers. While there are many solutions available for detecting malware on Android devices there aren’t that many that are concentrated on specific malware types. To this extent, this paper delivers a new dataset for Trojan detection for Android apps based on the permissions of the apps, while the second contribution is a neural network architecture that can classify with very high accuracy if an Android app is a genuine app or a Trojan pretending to be a normal app. We have run extensive evaluation tests to validate the performance of the proposed method and we have compared it to other well-known classifiers using well-known evaluation metrics to show its effectiveness.
Original languageEnglish
Title of host publicationInternational Conference on Engineering Applications of Neural Networks
Subtitle of host publicationEANN
PublisherSpringer
Pages203-212
Number of pages10
ISBN (Electronic)9783031082238
DOIs
Publication statusPublished - 10 Jun 2022

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
Volume1600

Keywords

  • Android
  • Malware detection
  • Trojan
  • Convolutional neural networks

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