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Deep Learning Techniques for Android Botnet Detection

https://doi.org/10.3390/electronics10040519

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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-319-25150-9_33openalex-snapshot

CAAL: Concurrency Workbench, Aalborg Edition

inferredcites →https://doi.org/10.1007/978-3-319-25645-0_6openalex-snapshot

Android Botnets: What URLs are Telling Us

inferredcites →https://doi.org/10.1007/978-3-642-24797-2_4openalex-snapshot

Long Short-Term Memory

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

Exploiting Model Checking for Mobile Botnet Detection

inferredcites →https://doi.org/10.1038/nature14539openalex-snapshot

Deep learning

inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot

Gradient-based learning applied to document recognition

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.2017.8074845openalex-snapshot

Improving dynamic analysis of android apps using hybrid test input generation

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/icact.2015.7224817openalex-snapshot

Cloud-based Android botnet malware detection system

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/iconac.2016.7604961openalex-snapshot

An enhanced botnet detection technique for mobile devices using log analysis

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/uic-atc-scalcom-cbdcom-iop.2015.240openalex-snapshot

DeDroid: A Mobile Botnet Detection Approach Based on Static Analysis

inferredcites →https://doi.org/10.1145/5397.5399openalex-snapshot

Automatic verification of finite-state concurrent systems using temporal logic specifications

inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot

Long Short-Term Memory

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

ABC: Android Botnet Classification Using Feature Selection and Classification Algorithms

inferredcites →https://doi.org/10.1186/s13635-019-0087-1openalex-snapshot

Machine learning-based dynamic analysis of Android apps with improved code coverage

inferredcites →https://doi.org/10.23919/icitst.2017.8356358openalex-snapshot

Android botnet detection: An integrated source code mining approach

inferredcites →https://doi.org/10.48550/arxiv.1705.06691openalex-snapshot

Improving Dynamic Analysis of Android Apps Using Hybrid Test Input Generation

What points at this work

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

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Detecting Botnets Through Deep Learning and Network Flow Analysis

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

BotDroid: Permission-Based Android Botnet Detection Using Neural Networks

inferred← citeshttps://doi.org/10.1007/978-3-032-14189-7_27openalex-snapshot

Botnet Detection in IoT Networks Using Hybrid Deep Learning CNN, LSTM, and GRU

inferred← citeshttps://doi.org/10.1007/978-981-99-7962-2_3openalex-snapshot

An Efficient Botnet Detection Using Machine Learning and Deep Learning

inferred← citeshttps://doi.org/10.1007/s00500-022-06750-4openalex-snapshot

RETRACTED ARTICLE: Hybrid deep-learning model to detect botnet attacks over internet of things environments

inferred← citeshttps://doi.org/10.1007/s00521-023-08512-1openalex-snapshot

MVDroid: an android malicious VPN detector using neural networks

inferred← citeshttps://doi.org/10.1007/s00521-024-10818-7openalex-snapshot

Zero-day Android botnet detection using neural networks

inferred← citeshttps://doi.org/10.1007/s10207-022-00624-4openalex-snapshot

Mobile botnet detection: a comprehensive survey

inferred← citeshttps://doi.org/10.1007/s10664-023-10302-1openalex-snapshot

Deep learning techniques to detect cybersecurity attacks: a systematic mapping study

inferred← citeshttps://doi.org/10.1007/s13198-024-02439-zopenalex-snapshot

Behavioral based detection of android ransomware using machine learning techniques

inferred← citeshttps://doi.org/10.1016/j.comcom.2025.108084openalex-snapshot

Deeply fused flow and topology features for botnet detection based on a pretrained GCN

inferred← citeshttps://doi.org/10.1016/j.compeleceng.2024.109233openalex-snapshot

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

inferred← citeshttps://doi.org/10.1016/j.eswa.2024.123384openalex-snapshot

Bot-DM: A dual-modal botnet detection method based on the combination of implicit semantic expression and graphical expression

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Hybrid deep learning models for road surface condition monitoring

inferred← citeshttps://doi.org/10.1080/23742917.2023.2247197openalex-snapshot

MadDroid: malicious adware detection in Android using deep learning

inferred← citeshttps://doi.org/10.1109/access.2022.3187094openalex-snapshot

Applications of Artificial Intelligence to Detect Android Botnets: A Survey

inferred← citeshttps://doi.org/10.1109/access.2024.3436588openalex-snapshot

Application of Deep Learning Models for Real-Time Automatic Malware Detection

inferred← citeshttps://doi.org/10.1109/aiccsa53542.2021.9686850openalex-snapshot

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

inferred← citeshttps://doi.org/10.1109/cicn56167.2022.10008248openalex-snapshot

Using Edge Devices and Machine Learning for Controlled Access to a Smart Campus

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inferred← citeshttps://doi.org/10.1109/icosec58147.2023.10276277openalex-snapshot

Deep Variational Auto Encoders for Botnet Attack Detection in Industrial Internet of Things

inferred← citeshttps://doi.org/10.1109/imcom53663.2022.9721811openalex-snapshot

Machine Learning for Multi-Classification of Botnets Attacks

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/isgteurope56780.2023.10407298openalex-snapshot

Energy Market Predictions with Hybrid Neural Network 1D-CNN-BiGRU

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

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inferred← citeshttps://doi.org/10.1109/jsyst.2023.3238678openalex-snapshot

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

inferred← citeshttps://doi.org/10.1109/siml65326.2025.11081101openalex-snapshot

Evaluation of Hybrid Deep Learning Models for Forecasting Chicken Egg Prices in Indonesia

inferred← citeshttps://doi.org/10.1109/tetci.2023.3281833openalex-snapshot

Android Malware Detection Methods Based on Convolutional Neural Network: A Survey

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A Hybrid GARCH and Deep Learning Method for Volatility Prediction

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Boosting credibility of a Recommender System using Deep Learning Techniques - An Empirical Study

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Forecasting Maximum Power Point in Solar Panels Using CNN-GRU

inferred← citeshttps://doi.org/10.17762/ijritcc.v10i1s.5899openalex-snapshot

A Hybrid Model for Android Malware Detection using Decision Tree and KNN

inferred← citeshttps://doi.org/10.21203/rs.3.rs-2555218/v1openalex-snapshot

Behavioural Based Detection of Android Ransomware Using Machine Learning Techniques

inferred← citeshttps://doi.org/10.21203/rs.3.rs-2630988/v1openalex-snapshot

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Mobile based Malware Detection using Artificial Intelligence Techniques a review

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Android Malware Detection Using ResNet-50 Stacking

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High Accuracy Detection of Mobile Malware Using Machine Learning

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Botnet Attack Detection Using Local Global Best Bat Algorithm for Industrial Internet of Things

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

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Malware Analysis in IoT & Android Systems with Defensive Mechanism

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