Android malware detection method based on byte-code image and deep learning

Android malware detection method based on byte-code image and deep learning

A new Android malware detection method based on byte-code image and deep learning was proposed. Firstly, Android malware byte-code files were mapped to RGB colorful images which had three channels. Also, the Shannon entropy as Alpha channel of images were calculated, and then merged with RGB images...

Full description

Saved in:

Bibliographic Details
Main Authors:	Tieming CHEN, Binbin XIANG, Mingqi LV, Bo CHEN, Xie JIANG
Format:	Article
Language:	zho
Published:	Beijing Xintong Media Co., Ltd 2019-01-01
Series:	Dianxin kexue
Subjects:	malware detection byte-code image Shannon entropy deep learning classification
Online Access:	http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000−0801.2019022/
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Android malware detection based on improved random forest
by: Hong-yu YANG, et al.
Published: (2017-04-01)

Android malware detection method based on SimHash
by: Bo CHEN, et al.
Published: (2017-11-01)

Android malware detection method based on deep neural network
by: Fan CHAO, et al.
Published: (2020-10-01)

Vehicle Flow Detection and Tracking Based on an Improved YOLOv8n and ByteTrack Framework
by: Jinjiang Liu, et al.
Published: (2024-12-01)

Review of malware detection and classification visualization techniques
by: Jinwei WANG, et al.
Published: (2023-10-01)

Android malware detection method based on combined algorithm
by: Hao CHEN, et al.
Published: (2016-10-01)

Transformer-based malware detection using process resource utilization metrics
by: Dimosthenis Natsos, et al.
Published: (2025-03-01)

Earthworm optimization algorithm based cascade LSTM-GRU model for android malware detection
by: Brij B. Gupta, et al.
Published: (2025-12-01)

MALVADA: A framework for generating datasets of malware execution traces
by: Razvan Raducu, et al.
Published: (2025-05-01)

Method of anti-confusion texture feature descriptor for malware images
by: Yashu LIU, et al.
Published: (2018-11-01)

LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
by: Durmus Ozkan Sahin, et al.
Published: (2022-01-01)

DLCDroid an android apps analysis framework to analyse the dynamically loaded code
by: Rati Bhan, et al.
Published: (2025-01-01)

Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques
by: Yadigar Imamverdiyev, et al.
Published: (2025-01-01)

Android malware detection method based on permission sequential pattern mining algorithm
by: Huan YANG, et al.
Published: (2013-08-01)

PermGuard: A Scalable Framework for Android Malware Detection Using Permission-to-Exploitation Mapping
by: Arvind Prasad, et al.
Published: (2025-01-01)

Android malware family classification method based on the image of bytecodeConstruction of MDS matrices
by: Yi-min YANG, et al.
Published: (2016-06-01)

Landslide hazard zonation using of model Shannon entropy(case study: Taleghan watershed)
by: Mehdi feyzolahpour, et al.
Published: (2021-09-01)

Research on Operators Mobile Malware Protection Architecture and Key Technologies
by: Tao Chen, et al.
Published: (2014-01-01)

Apk2Audio4AndMal: Audio Based Malware Family Detection Framework
by: Oguz Emre Kural, et al.
Published: (2023-01-01)

Research on Anti-Trojan Malware Mechanism Based on Characteristic Behavior
by: Weifu Zou, et al.
Published: (2014-11-01)

A novel feature selection technique: Detection and classification of Android malware
by: Sandeep Sharma, et al.
Published: (2025-03-01)

Android Malware Threats: A Strengthened Reverse Engineering Approach to Forensic Analysis
by: Ridho Surya Kusuma, et al.
Published: (2025-01-01)

Malware classification method based on static multiple-feature fusion
by: Bo-wen SUN, et al.
Published: (2017-11-01)

Malware detection approach based on improved SOINN
by: Bin ZHANG, et al.
Published: (2019-12-01)

Transforming Weakness into Strength: Improving Unreliable Malware Detection Methods
by: Pavel Novak, et al.
Published: (2024-12-01)

HoneyBow:an automated malware collection tool based on the high-interaction honeypot principle
by: ZHUGE Jian-wei1, et al.
Published: (2007-01-01)

A Survey on Adversarial Attacks for Malware Analysis
by: Kshitiz Aryal, et al.
Published: (2025-01-01)

IMCMK-CNN: A lightweight convolutional neural network with Multi-scale Kernels for Image-based Malware Classification
by: Dandan Zhang, et al.
Published: (2025-01-01)

Deep visualization classification method for malicious code based on Ngram-TFIDF
by: WANG Jinwei, et al.
Published: (2024-06-01)

MalHAPGNN: An Enhanced Call Graph-Based Malware Detection Framework Using Hierarchical Attention Pooling Graph Neural Network
by: Wenjie Guo, et al.
Published: (2025-01-01)

Mobile malware traffic detection approach based on value-derivative GRU
by: Hanxun ZHOU, et al.
Published: (2020-01-01)

FABLDroid: Malware detection based on hybrid analysis with factor analysis and broad learning methods for android applications
by: Kazım Kılıç, et al.
Published: (2025-02-01)

Multi-feature fusion malware detection method based on attention and gating mechanisms
by: Zhongyuan CHEN, et al.
Published: (2024-02-01)

A byte-size multi-variable-length-code based string matching algorithm for Alpha image coding
by: Liping ZHAO, et al.
Published: (2018-11-01)

Integrating Information Gain and Chi-Square for Enhanced Malware Detection Performance
by: Fauzi Adi Rafrastara, et al.
Published: (2025-01-01)

Study on modern malware analysis system
by: Yi ZHAO, et al.
Published: (2014-10-01)

Survival Copula Entropy and Dependence in Bivariate Distributions
by: S.M. Sunoj, et al.
Published: (2025-01-01)

Advanced Malware Detection: Integrating Convolutional Neural Networks with LSTM RNNs for Enhanced Security
by: Balsam Ridha Habeeb Alsaedi
Published: (2024-12-01)

Symbolic dynamics, entropy and complexity of the feigenbaum map at the accumulation point
by: Werner Ebelings, et al.
Published: (1998-01-01)

Research on the reverse analyses and monitoring data of Mirai malware botnet
by: Ya-liang CHEN, et al.
Published: (2017-08-01)