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A Novel Android Botnet Detection System Using Image-Based and Manifest File Features

https://doi.org/10.3390/electronics11030486

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Recognition of Facial Expressions Based on Detection of Facial Components and HOG Characteristics

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Malware analysis using visualized images and entropy graphs

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A smart adaptive particle swarm optimization–support vector machine: android botnet detection application

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IMCFN: Image-based malware classification using fine-tuned convolutional neural network architecture

inferredcites →https://doi.org/10.1016/j.cose.2020.101748openalex-snapshot

Image-Based malware classification using ensemble of CNN architectures (IMCEC)

inferredcites →https://doi.org/10.1016/j.cose.2020.102166openalex-snapshot

Catch them alive: A malware detection approach through memory forensics, manifold learning and computer vision

inferredcites →https://doi.org/10.1016/j.diin.2018.09.006openalex-snapshot

A malware classification method based on memory dump grayscale image

inferredcites →https://doi.org/10.1016/j.future.2017.01.019openalex-snapshot

Detecting Android malicious apps and categorizing benign apps with ensemble of classifiers

inferredcites →https://doi.org/10.1016/j.jksuci.2018.05.010openalex-snapshot

Feature selection using an improved Chi-square for Arabic text classification

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MalFCS: An effective malware classification framework with automated feature extraction based on deep convolutional neural networks

inferredcites →https://doi.org/10.1016/j.procs.2019.09.263openalex-snapshot

Exploiting Model Checking for Mobile Botnet Detection

inferredcites →https://doi.org/10.1049/cje.2018.05.001openalex-snapshot

Automatic Malware Classification via PRICoLBP

inferredcites →https://doi.org/10.1109/34.683777openalex-snapshot

Support vector machines for 3D object recognition

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Small sample error rate estimation for k-NN classifiers

inferredcites →https://doi.org/10.1109/access.2018.2844349openalex-snapshot

A Novel Dynamic Android Malware Detection System With Ensemble Learning

inferredcites →https://doi.org/10.1109/access.2020.3006143openalex-snapshot

A Review of Android Malware Detection Approaches Based on Machine Learning

inferredcites →https://doi.org/10.1109/access.2020.3013699openalex-snapshot

AI Meta-Learners and Extra-Trees Algorithm for the Detection of Phishing Websites

inferredcites →https://doi.org/10.1109/aiccsa53542.2021.9686850openalex-snapshot

Bot-IMG: A framework for image-based detection of Android botnets using machine learning

inferredcites →https://doi.org/10.1109/bigdata.2017.8258512openalex-snapshot

Binary malware image classification using machine learning with local binary pattern

inferredcites →https://doi.org/10.1109/bigdata47090.2019.9006586openalex-snapshot

Application of XGBoost to the cyber-security problem of detecting suspicious network traffic events

inferredcites →https://doi.org/10.1109/cicybs.2013.6597204openalex-snapshot

Image visualization based malware detection

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AE-DCNN: Autoencoder Enhanced Deep Convolutional Neural Network For Malware Classification

inferredcites →https://doi.org/10.1109/cybersa49311.2020.9139664openalex-snapshot

Mobile Botnet Detection: A Deep Learning Approach Using Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/cybersecpods.2019.8885384openalex-snapshot

Longitudinal performance analysis of machine learning based Android malware detectors

inferredcites →https://doi.org/10.1109/est.2017.8090410openalex-snapshot

A new mobile botnet classification based on permission and API calls

inferredcites →https://doi.org/10.1109/icact.2015.7224817openalex-snapshot

Cloud-based Android botnet malware detection system

inferredcites →https://doi.org/10.1109/icccbda.2017.7951933openalex-snapshot

Malware variants detection based on opcode image recognition in small training set

inferredcites →https://doi.org/10.1109/iced.2016.7804708openalex-snapshot

A static approach towards mobile botnet detection

inferredcites →https://doi.org/10.1109/icee50131.2020.9260674openalex-snapshot

Android Botnet Detection using Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/icramet53537.2021.9650473openalex-snapshot

HOG Based Pedestrian Detection System for Autonomous Vehicle Operated in Limited Area

inferredcites →https://doi.org/10.1109/ict-ispc.2016.7519221openalex-snapshot

ABIS: A prototype of Android Botnet Identification System

inferredcites →https://doi.org/10.1109/ictcs.2017.48openalex-snapshot

Toward a Detection Framework for Android Botnet

inferredcites →https://doi.org/10.1109/pst.2015.7232968openalex-snapshot

Real-time signature-based detection approach for SMS botnet

inferredcites →https://doi.org/10.1109/siu.2019.8806511openalex-snapshot

Utilization and Comparision of Convolutional Neural Networks in Malware Recognition

inferredcites →https://doi.org/10.1109/tsmcc.2008.923876openalex-snapshot

Random-Forests-Based Network Intrusion Detection Systems

inferredcites →https://doi.org/10.1109/uic-atc-scalcom-cbdcom-iop.2015.240openalex-snapshot

DeDroid: A Mobile Botnet Detection Approach Based on Static Analysis

inferredcites →https://doi.org/10.1145/2016904.2016908openalex-snapshot

Malware images

inferredcites →https://doi.org/10.1145/2046684.2046689openalex-snapshot

A comparative assessment of malware classification using binary texture analysis and dynamic analysis

inferredcites →https://doi.org/10.1166/asl.2017.8994openalex-snapshot

ABC: Android Botnet Classification Using Feature Selection and Classification Algorithms

inferredcites →https://doi.org/10.14419/ijet.v7i4.15.21429openalex-snapshot

Mobile Botnet Classification by using Hybrid Analysis

inferredcites →https://doi.org/10.3390/app11146446openalex-snapshot

Visualized Malware Multi-Classification Framework Using Fine-Tuned CNN-Based Transfer Learning Models

inferredcites →https://doi.org/10.3390/e23030344openalex-snapshot

An Efficient DenseNet-Based Deep Learning Model for Malware Detection

inferredcites →https://doi.org/10.3390/electronics10040519openalex-snapshot

Deep Learning Techniques for Android Botnet Detection

inferredcites →https://doi.org/10.3390/electronics10131606openalex-snapshot

Android Mobile Malware Detection Using Machine Learning: A Systematic Review

inferredcites →https://doi.org/10.3390/electronics10192444openalex-snapshot

Image-Based Malware Classification Using VGG19 Network and Spatial Convolutional Attention

inferredcites →https://doi.org/10.3390/s20247013openalex-snapshot

Deep Feature Extraction and Classification of Android Malware Images

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Electro search optimization based long short‐term memory network for mobile malware detection

inferred← citeshttps://doi.org/10.1002/spy2.494openalex-snapshot

Mobile Botnet Attacks Detection Using Supervised Learning Algorithms

inferred← citeshttps://doi.org/10.1007/978-3-031-34204-2_7openalex-snapshot

BotDroid: Permission-Based Android Botnet Detection Using Neural Networks

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Zero-day Android botnet detection using neural networks

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Malware classification approaches utilizing binary and text encoding of permissions

inferred← citeshttps://doi.org/10.1007/s10791-026-09987-xopenalex-snapshot

Attention based CNN-transformer ensemble for multiclass botnet detection in industrial IoT networks

inferred← citeshttps://doi.org/10.1016/j.aej.2025.01.042openalex-snapshot

A novel feature selection-driven ensemble learning approach for accurate botnet attack detection

inferred← citeshttps://doi.org/10.1016/j.compeleceng.2023.108804openalex-snapshot

DroidEncoder: Malware detection using auto-encoder based feature extractor and machine learning algorithms

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Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey

inferred← citeshttps://doi.org/10.1016/j.jiixd.2025.12.004openalex-snapshot

HTA-BotDef: A novel hierarchical tree aggregation for scalable and privacy preserving botnet attack detection with federated learning

inferred← citeshttps://doi.org/10.1038/s41598-023-48230-1openalex-snapshot

A novel hybrid feature selection and ensemble-based machine learning approach for botnet detection

inferred← citeshttps://doi.org/10.1080/23742917.2026.2628020openalex-snapshot

A systematic review on botnet defense mechanisms: past, present and future

inferred← citeshttps://doi.org/10.1109/cicn63059.2024.10847448openalex-snapshot

Botnet Detection Using Network Traffic Visualization and Histogram of Oriented Gradients

inferred← citeshttps://doi.org/10.1109/ibcast59916.2023.10713040openalex-snapshot

Improving Botnet Detection with a Generative Adversarial Network-Based Technique

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A Hybrid Approach to Detect Botnet Attacks in IoT Environments using Machine Learning

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A Comprehensive IDs to Detect Botnet Attacks Using Machine Learning Techniques

inferred← citeshttps://doi.org/10.1109/icocics58778.2023.10277440openalex-snapshot

Image-Based Malware Classification: A Systematic Literature Review

inferred← citeshttps://doi.org/10.1109/iconstem60960.2024.10568802openalex-snapshot

Detecting and comparing the accuracy of Retweetering Bot using Transition Probability-LSTM with AlexNet

inferred← citeshttps://doi.org/10.1109/ignite69592.2026.11705783openalex-snapshot

MM-IoTGuard: A Multi-Modality driven Framework for IoT Botnet Detection

inferred← citeshttps://doi.org/10.1109/isdfs55398.2022.9800817openalex-snapshot

A deep learning-enhanced botnet detection system based on Android manifest text mining

inferred← citeshttps://doi.org/10.1109/iske60036.2023.10481346openalex-snapshot

Efficient IoT Malware Detection Using Convolution Neural Network and View-Invariant Block

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Obfuscated Malware Detection in IoT Android Applications Using Markov Images and CNN

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Performance Evaluation of Botnet Attack Detection Using XAI

inferred← citeshttps://doi.org/10.32604/cmes.2023.029911openalex-snapshot

Terrorism Attack Classification Using Machine Learning: The Effectiveness of Using Textual Features Extracted from GTD Dataset

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High Accuracy Detection of Mobile Malware Using Machine Learning

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Malware Analysis in IoT & Android Systems with Defensive Mechanism

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High Accuracy Detection of Mobile Malware Using Machine Learning

inferred← citeshttps://doi.org/10.3390/eng4010039openalex-snapshot

Ensemble Machine Learning Techniques for Accurate and Efficient Detection of Botnet Attacks in Connected Computers

inferred← citeshttps://doi.org/10.3934/era.2024192openalex-snapshot

Employing combined spatial and frequency domain image features for machine learning-based malware detection

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Feature Engineering and Computer Vision for Cybersecurity

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