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Assessing and Improving Malware Detection Sustainability through App Evolution Studies
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-04283-1_6openalex-snapshot
DroidAPIMiner: Mining API-Level Features for Robust Malware Detection in Android
inferredcites →https://doi.org/10.1007/978-3-319-11203-9_10openalex-snapshot
DroidMiner: Automated Mining and Characterization of Fine-grained Malicious Behaviors in Android Applications
inferredcites →https://doi.org/10.1007/978-3-319-26362-5_18openalex-snapshot
HelDroid: Dissecting and Detecting Mobile Ransomware
inferredcites →https://doi.org/10.1007/s10844-010-0148-xopenalex-snapshot
“Andromaly”: a behavioral malware detection framework for android devices
inferredcites →https://doi.org/10.1007/s11416-014-0226-7openalex-snapshot
Identifying Android malware using dynamically obtained features
inferredcites →https://doi.org/10.1007/s11416-015-0244-0openalex-snapshot
Behavior-based features model for malware detection
inferredcites →https://doi.org/10.1016/j.cose.2015.02.007openalex-snapshot
Stealth attacks: An extended insight into the obfuscation effects on Android malware
inferredcites →https://doi.org/10.1016/j.eswa.2018.03.021openalex-snapshot
Adapting dynamic classifier selection for concept drift
inferredcites →https://doi.org/10.1109/ase.2015.89openalex-snapshot
Automated Test Input Generation for Android: Are We There Yet? (E)
inferredcites →https://doi.org/10.1109/asiajcis.2012.18openalex-snapshot
DroidMat: Android Malware Detection through Manifest and API Calls Tracing
inferredcites →https://doi.org/10.1109/compsac.2015.103openalex-snapshot
MARVIN: Efficient and Comprehensive Mobile App Classification through Static and Dynamic Analysis
inferredcites →https://doi.org/10.1109/comst.2014.2386139openalex-snapshot
Android Security: A Survey of Issues, Malware Penetration, and Defenses
inferredcites →https://doi.org/10.1109/icse-companion.2019.00110openalex-snapshot
On the Deterioration of Learning-Based Malware Detectors for Android
inferredcites →https://doi.org/10.1109/icse.2015.61openalex-snapshot
Mining Apps for Abnormal Usage of Sensitive Data
inferredcites →https://doi.org/10.1109/icse.2017.35openalex-snapshot
Making Malory Behave Maliciously: Targeted Fuzzing of Android Execution Environments
inferredcites →https://doi.org/10.1109/icse.2017.65openalex-snapshot
Automatic Text Input Generation for Mobile Testing
inferredcites →https://doi.org/10.1109/icsme.2017.31openalex-snapshot
Understanding Android Application Programming and Security: A Dynamic Study
inferredcites →https://doi.org/10.1109/icsme.2017.35openalex-snapshot
DroidFax: A Toolkit for Systematic Characterization of Android Applications
inferredcites →https://doi.org/10.1109/icsme.2017.36openalex-snapshot
Artifacts for Dynamic Analysis of Android Apps
inferredcites →https://doi.org/10.1109/icsme.2017.74openalex-snapshot
Dissecting Android Inter-component Communications via Interactive Visual Explorations
inferredcites →https://doi.org/10.1109/jsac.2002.806121openalex-snapshot
Language-based information-flow security
inferredcites →https://doi.org/10.1109/sp.2012.16openalex-snapshot
Dissecting Android Malware: Characterization and Evolution
inferredcites →https://doi.org/10.1109/spw.2016.25openalex-snapshot
DroidScribe: Classifying Android Malware Based on Runtime Behavior
inferredcites →https://doi.org/10.1109/tdsc.2016.2536605openalex-snapshot
MADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention
inferredcites →https://doi.org/10.1109/tetci.2017.2699220openalex-snapshot
Context-Aware, Adaptive, and Scalable Android Malware Detection Through Online Learning
inferredcites →https://doi.org/10.1109/tifs.2016.2523912openalex-snapshot
ICCDetector: ICC-Based Malware Detection on Android
inferredcites →https://doi.org/10.1109/tifs.2018.2879302openalex-snapshot
DroidCat: Effective Android Malware Detection and Categorization via App-Level Profiling
inferredcites →https://doi.org/10.1109/tmc.2018.2861405openalex-snapshot
Android Malware Detection Using Complex-Flows
inferredcites →https://doi.org/10.1109/tmc.2018.2889495openalex-snapshot
Identifying Mobile Inter-App Communication Risks
inferredcites →https://doi.org/10.1145/2568225.2568276openalex-snapshot
Checking app behavior against app descriptions
inferredcites →https://doi.org/10.1145/2635868.2635869openalex-snapshot
Apposcopy: semantics-based detection of Android malware through static analysis
inferredcites →https://doi.org/10.1145/2660267.2660359openalex-snapshot
Semantics-Aware Android Malware Classification Using Weighted Contextual API Dependency Graphs
inferredcites →https://doi.org/10.1145/2897073.2897707openalex-snapshot
Pinpointing mobile malware using code analysis
inferredcites →https://doi.org/10.1145/3017427openalex-snapshot
The Evolution of Android Malware and Android Analysis Techniques
inferredcites →https://doi.org/10.1145/3162625openalex-snapshot
Lightweight, Obfuscation-Resilient Detection and Family Identification of Android Malware
inferredcites →https://doi.org/10.1145/3180155.3180228openalex-snapshot
A large-scale empirical study on the effects of code obfuscations on Android apps and anti-malware products
inferredcites →https://doi.org/10.1145/3183440.3195004openalex-snapshot
Towards sustainable Android malware detection
inferredcites →https://doi.org/10.1145/3194733.3194742openalex-snapshot
On the effectiveness of random testing for Android
inferredcites →https://doi.org/10.1145/3196398.3196433openalex-snapshot
Leveraging historical versions of Android apps for efficient and precise taint analysis
inferredcites →https://doi.org/10.14722/ndss.2014.23039openalex-snapshot
A Machine-learning Approach for Classifying and Categorizing Android Sources and Sinks
inferredcites →https://doi.org/10.14722/ndss.2014.23247openalex-snapshot
Drebin: Effective and Explainable Detection of Android Malware in Your Pocket
inferredcites →https://doi.org/10.14722/ndss.2015.23145openalex-snapshot
CopperDroid: Automatic Reconstruction of Android Malware Behaviors
inferredcites →https://doi.org/10.4324/9781315806730openalex-snapshot
Ordinal Methods for Behavioral Data Analysis
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.48550/arxiv.1503.07217openalex-snapshot
Automated Test Input Generation for Android: Are We There Yet?
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/ett.4840openalex-snapshot
MUDROID: Android malware detection and classification based on permission and behavior for autonomous vehicles
inferred← citeshttps://doi.org/10.1002/spy2.347openalex-snapshot
DeepMDFC : A deep learning based android malware detection and family classification method
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Security Defect Identification of Android Applications by Permission Extraction using Machine Learning
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Longitudinal Evaluation of Android Malware Detection Using Deep Learning Classifiers
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Enabling Android Application Monitoring by Characterizing Security-Critical Code Fragments
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AnGSL: Graph-Based Android Malware Detection Method
inferred← citeshttps://doi.org/10.1007/978-981-96-2417-1_21openalex-snapshot
Malware Variant Detection Based on Knowledge Transfer and Ensemble Learning
inferred← citeshttps://doi.org/10.1007/978-981-97-5663-6_4openalex-snapshot
LIFT: Discriminant Classification Approach of Malware Family on Time Consistent Open Set
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Enhanced android adware detection using optimized catboost and sparse autoencoder
inferred← citeshttps://doi.org/10.1007/s10664-021-09955-7openalex-snapshot
Lessons Learnt on Reproducibility in Machine Learning Based Android Malware Detection
inferred← citeshttps://doi.org/10.1007/s10664-023-10375-yopenalex-snapshot
Experimental comparison of features, analyses, and classifiers for Android malware detection
inferred← citeshttps://doi.org/10.1007/s11416-021-00410-1openalex-snapshot
An efficient IDS in cloud environment using feature selection based on DM algorithm
inferred← citeshttps://doi.org/10.1016/j.cose.2021.102399openalex-snapshot
KronoDroid: Time-based Hybrid-featured Dataset for Effective Android Malware Detection and Characterization
inferred← citeshttps://doi.org/10.1016/j.cose.2022.102757openalex-snapshot
Concept drift and cross-device behavior: Challenges and implications for effective android malware detection
inferred← citeshttps://doi.org/10.1016/j.cose.2022.102835openalex-snapshot
On the relativity of time: Implications and challenges of data drift on long-term effective android malware detection
inferred← citeshttps://doi.org/10.1016/j.cose.2023.103654openalex-snapshot
Machine Learning for Android Malware Detection: Mission Accomplished? A Comprehensive Review of Open Challenges and Future Perspectives
inferred← citeshttps://doi.org/10.1016/j.cose.2024.103969openalex-snapshot
MaDroid: A maliciousness-aware multifeatured dataset for detecting android malware
inferred← citeshttps://doi.org/10.1016/j.cose.2024.104294openalex-snapshot
LDCDroid: Learning data drift characteristics for handling the model aging problem in Android malware detection
inferred← citeshttps://doi.org/10.1016/j.cosrev.2026.100914openalex-snapshot
Security through the eyes of AI: How visualization is shaping malware detection
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.117200openalex-snapshot
Android malware concept drift using system calls: Detection, characterization and challenges
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.118404openalex-snapshot
Behaviour analysis of inter-app communication using a lightweight monitoring app for malware detection
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.118590openalex-snapshot
Fast & Furious: Modelling Malware Detection as Evolving Data Streams
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.118724openalex-snapshot
An effectiveness analysis of transfer learning for the concept drift problem in malware detection
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.122255openalex-snapshot
Detection approaches for android malware: Taxonomy and review analysis
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.129446openalex-snapshot
CADroid: A cross-combination attention based framework for android malware detection
inferred← citeshttps://doi.org/10.1016/j.infsof.2020.106291openalex-snapshot
A study of run-time behavioral evolution of benign versus malicious apps in android
inferred← citeshttps://doi.org/10.1016/j.jer.2024.04.008openalex-snapshot
Machine learning approach to detect android malware using feature-selection based on feature importance score
inferred← citeshttps://doi.org/10.1016/j.jisa.2021.103063openalex-snapshot
DTMIC: Deep transfer learning for malware image classification
inferred← citeshttps://doi.org/10.1016/j.jisa.2021.103098openalex-snapshot
Towards time evolved malware identification using two-head neural network
inferred← citeshttps://doi.org/10.1016/j.jisa.2023.103556openalex-snapshot
WHGDroid: Effective android malware detection based on weighted heterogeneous graph
inferred← citeshttps://doi.org/10.1016/j.jisa.2023.103617openalex-snapshot
Maaker: A framework for detecting and defeating evasion techniques in Android malware
inferred← citeshttps://doi.org/10.1049/cmu2.12754openalex-snapshot
An effective attention and residual network for malware detection
inferred← citeshttps://doi.org/10.1049/ise2.12082openalex-snapshot
DeepCatra: Learning flow‐ and graph‐based behaviours for Android malware detection
inferred← citeshttps://doi.org/10.1080/01969722.2021.2020471openalex-snapshot
On the Effectiveness of Image Processing Based Malware Detection Techniques
inferred← citeshttps://doi.org/10.1080/08839514.2021.2007327openalex-snapshot
A Systematic Overview of Android Malware Detection
inferred← citeshttps://doi.org/10.1088/1742-6596/1911/1/012031openalex-snapshot
Android Malware Detection and Classification using LOFO Feature Selection and Tree-based Models
inferred← citeshttps://doi.org/10.1093/comjnl/bxag091openalex-snapshot
Enhanced AI-driven zero-shot learning for Android malware detection with hybrid clustering
inferred← citeshttps://doi.org/10.1109/access.2020.3006143openalex-snapshot
A Review of Android Malware Detection Approaches Based on Machine Learning
inferred← citeshttps://doi.org/10.1109/access.2021.3082173openalex-snapshot
DAEMON: Dataset/Platform-Agnostic Explainable Malware Classification Using Multi-Stage Feature Mining
inferred← citeshttps://doi.org/10.1109/access.2021.3123187openalex-snapshot
Recent Advances in Android Mobile Malware Detection: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1109/access.2021.3139334openalex-snapshot
Efficient Deep Learning Network With Multi-Streams for Android Malware Family Classification
inferred← citeshttps://doi.org/10.1109/access.2022.3149053openalex-snapshot
Malware Detection: A Framework for Reverse Engineered Android Applications Through Machine Learning Algorithms
inferred← citeshttps://doi.org/10.1109/access.2022.3217795openalex-snapshot
Smishing Strategy Dynamics and Evolving Botnet Activities in Japan
inferred← citeshttps://doi.org/10.1109/access.2024.3486094openalex-snapshot
Performance-Oriented and Sustainability-Oriented Design of an Effective Android Malware Detector
inferred← citeshttps://doi.org/10.1109/access.2025.3576733openalex-snapshot
Enhancing the Sustainability of Machine Learning-Based Malware Detection Techniques for Android Applications
inferred← citeshttps://doi.org/10.1109/access.2025.3589656openalex-snapshot
A Robust and Efficient Machine Learning Framework for Enhancing Early Detection of Android Malware
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Emerging Ransomware Attacks: Improvement and Remedies - A Systematic Literature Review
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Sustainability of Machine Learning-based Android Malware Detection Using API calls and Permissions
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inferred← citeshttps://doi.org/10.1109/issre62328.2024.00012openalex-snapshot
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An Adversarial Robust Behavior Sequence Anomaly Detection Approach Based on Critical Behavior Unit Learning
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Debiasing Android Malware Datasets: How Can I Trust Your Results If Your Dataset Is Biased?
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DeepVMUnProtect: Neural Network-Based Recovery of VM-Protected Android Apps for Semantics-Aware Malware Detection
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AndroZoo: A Retrospective with a Glimpse into the Future
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SoK: Visualization-based Malware Detection Techniques
inferred← citeshttps://doi.org/10.1145/3664806openalex-snapshot
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LLM-Explorer: Towards Efficient and Affordable LLM-based Exploration for Mobile Apps
inferred← citeshttps://doi.org/10.1145/3708476openalex-snapshot
DistMeasure : A Framework for Runtime Characterization and Quality Assessment of Distributed Software via Interprocess Communications
inferred← citeshttps://doi.org/10.1145/3708500openalex-snapshot
Characterization of Android Malwares and their families
inferred← citeshttps://doi.org/10.1145/3720541openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3725810openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3743132openalex-snapshot
EvoTaint : Incremental Static Taint Analysis of Evolving Android Apps
inferred← citeshttps://doi.org/10.1145/3799692openalex-snapshot
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The Illusion of Success: Learning-Based Android Malware Detectors (Replicability Study)
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Android Malware Detection via Graph Representation Learning
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Fisher exact Boschloo and polynomial vector learning for malware detection
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inferred← citeshttps://doi.org/10.1186/s42400-022-00119-8openalex-snapshot
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Empirical Analysis of Learning-based Malware Detection Methods using Image Visualization
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inferred← citeshttps://doi.org/10.2139/ssrn.5519478openalex-snapshot
A Systematic Survey of Android Malware Detection Through Learning-Based Technology
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EAODroid: Android Malware Detection Based on Enhanced API Order
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Android malware detection using PMCC heatmap and Fuzzy Unordered Rule Induction Algorithm (FURIA)
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Machine-Learning-Based Android Malware Family Classification Using Built-In and Custom Permissions
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A Novel Monte-Carlo Simulation-Based Model for Malware Detection (eRBCM)
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Malware Identification Method in Industrial Control Systems Based on Opcode2vec and CVAE-GAN
inferred← citeshttps://doi.org/10.3390/sym14061178openalex-snapshot
Early Detection of Abnormal Attacks in Software-Defined Networking Using Machine Learning Approaches
inferred← citeshttps://doi.org/10.3934/era.2024192openalex-snapshot
Employing combined spatial and frequency domain image features for machine learning-based malware detection
inferred← citeshttps://doi.org/10.4018/979-8-3373-4154-5.ch011openalex-snapshot
A Parallel Ensemble Machine Learning System for Android Mobile Endpoint Malware Detection
inferred← citeshttps://doi.org/10.52700/jn.v4i2.90openalex-snapshot
Effectiveness Of Detecting Android Malware Using Deep Learning Techniques
inferred← citeshttps://doi.org/10.70675/f9b82129z4dffz465ezb079z0a85d72432d3openalex-snapshot
Profiling and Visualizing Android Malware Datasets
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