A Method for Automatic Android Malware Detection Based on Static Analysis and Deep Learning-Reference-Cited by-同舟云学术

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A Method for Automatic Android Malware Detection Based on Static Analysis and Deep Learning

Published:2022 Issue: Volume:10 Page:117334-117352
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ibrahim Mulhem¹^ORCID,Issa Bayan²^ORCID,Jasser Muhammed Basheer³^ORCID

Affiliation:

1. Department of Computer Engineering, Faculty of Engineering, Turkish-German University, Beykoz, Istanbul, Turkey

2. Faculty of Informatics Engineering, University of Aleppo, Aleppo, Syria

3. Department of Computing and Information Systems, School of Engineering and Technology, Sunway University, Petaling Jaya, Selangor, Malaysia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09936621.pdf?arnumber=9936621

Reference66 articles.

1. Malware Classification using Long Short-term Memory Models

2. BLADE: Robust malware detection against obfuscation in android

3. Permission-based Android malware detection;aung;Int J Sci Technol Res,2013

4. Android malware classification based on ANFIS with fuzzy c-means clustering using significant application permissions

5. Detecting Malware for Android Platform: An SVM-Based Approach

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1. TDBAMLA: Temporal and dynamic behavior analysis in Android malware using LSTM and attention mechanisms;Computer Standards & Interfaces;2025-03

2. PHIGrader: Evaluating the effectiveness of Manifest file components in Android malware detection using Multi Criteria Decision Making techniques;Journal of Network and Computer Applications;2024-12

3. Detection of Evasive Android Malware Using EigenGCN;Journal of Information Security and Applications;2024-11

4. SNDGCN: Robust Android malware detection based on subgraph network and denoising GCN network;Expert Systems with Applications;2024-09

5. An Enhanced Framework to Mitigate Post-Installation Cyber Attacks on Android Apps;Engineering, Technology & Applied Science Research;2024-08-02

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