On the public citation graph
A Malware Detection Approach Using Autoencoder in Deep Learning
0 signed · 160 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-1-4302-4681-7_30openalex-snapshot
Deploying Your Application: Google Play Store and Beyond
inferredcites →https://doi.org/10.1007/978-981-15-1304-6_27openalex-snapshot
AI and Its Risks in Android Smartphones: A Case of Google Smart Assistant
inferredcites →https://doi.org/10.1007/s12652-018-0803-6openalex-snapshot
Effective android malware detection with a hybrid model based on deep autoencoder and convolutional neural network
inferredcites →https://doi.org/10.1016/j.cose.2015.12.005openalex-snapshot
Andro-Dumpsys: Anti-malware system based on the similarity of malware creator and malware centric information
inferredcites →https://doi.org/10.1016/j.cose.2019.101663openalex-snapshot
DL-Droid: Deep learning based android malware detection using real devices
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.future.2018.09.042openalex-snapshot
An adaptive and configurable protection framework against android privilege escalation threats
inferredcites →https://doi.org/10.1016/j.jksuci.2017.01.003openalex-snapshot
A learning model to detect maliciousness of portable executable using integrated feature set
inferredcites →https://doi.org/10.1016/j.jpdc.2019.11.001openalex-snapshot
Malware detection in mobile environments based on Autoencoders and API-images
inferredcites →https://doi.org/10.1016/j.procs.2016.02.006openalex-snapshot
Android Applications Repackaging Detection Techniques for Smartphone Devices
inferredcites →https://doi.org/10.1049/iet-ifs.2013.0095openalex-snapshot
Analysis of Bayesian classification‐based approaches for Android malware detection
inferredcites →https://doi.org/10.1109/access.2021.3089586openalex-snapshot
A New Malware Classification Framework Based on Deep Learning Algorithms
inferredcites →https://doi.org/10.1109/ase.2019.00155openalex-snapshot
An Image-Inspired and CNN-Based Android Malware Detection Approach
inferredcites →https://doi.org/10.1109/bigdata.2018.8622324openalex-snapshot
R2-D2: ColoR-inspired Convolutional NeuRal Network (CNN)-based AndroiD Malware Detections
inferredcites →https://doi.org/10.1109/cloud.2018.00028openalex-snapshot
Malware Detection in Cloud Infrastructures Using Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/compsac.2016.151openalex-snapshot
Malware Detection with Deep Neural Network Using Process Behavior
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cyberc.2015.88openalex-snapshot
Android Malware Detection Based on Static Analysis of Characteristic Tree
inferredcites →https://doi.org/10.1109/icassp.2015.7178304openalex-snapshot
Malware classification with recurrent networks
inferredcites →https://doi.org/10.1109/icassp.2017.7952603openalex-snapshot
Malware classification with LSTM and GRU language models and a character-level CNN
inferredcites →https://doi.org/10.1109/iccnc.2013.6504162openalex-snapshot
Automated malware classification based on network behavior
inferredcites →https://doi.org/10.1109/iccnc.2018.8390391openalex-snapshot
An Android Malware Detection Approach Using Weight-Adjusted Deep Learning
inferredcites →https://doi.org/10.1109/icmla.2019.00076openalex-snapshot
RNN-Based Classifier to Detect Stealthy Malware using Localized Features and Complex Symbolic Sequence
inferredcites →https://doi.org/10.1109/icsess.2017.8342924openalex-snapshot
Detecting environment-sensitive malware based on taint analysis
inferredcites →https://doi.org/10.1109/ijcnn.2017.7966078openalex-snapshot
Classification of Android apps and malware using deep neural networks
inferredcites →https://doi.org/10.1109/iwcmc.2013.6583806openalex-snapshot
Applying machine learning classifiers to dynamic Android malware detection at scale
inferredcites →https://doi.org/10.1109/iwcmc48107.2020.9148289openalex-snapshot
LGMal: A Joint Framework Based on Local and Global Features for Malware Detection
inferredcites →https://doi.org/10.1109/ntms.2016.7792435openalex-snapshot
ANASTASIA: ANdroid mAlware detection using STatic analySIs of Applications
inferredcites →https://doi.org/10.1109/sarnof.2016.7846747openalex-snapshot
DroidDeepLearner: Identifying Android malware using deep learning
inferredcites →https://doi.org/10.1109/secpri.2001.924286openalex-snapshot
Data mining methods for detection of new malicious executables
inferredcites →https://doi.org/10.1109/smartiot.2018.00034openalex-snapshot
Quick and Accurate Android Malware Detection Based on Sensitive APIs
inferredcites →https://doi.org/10.1109/synasc.2016.057openalex-snapshot
Malware Classification Based on Dynamic Behavior
inferredcites →https://doi.org/10.1109/tase.2018.00015openalex-snapshot
RepassDroid: Automatic Detection of Android Malware Based on Essential Permissions and Semantic Features of Sensitive APIs
inferredcites →https://doi.org/10.1109/tifs.2018.2866319openalex-snapshot
A Multimodal Deep Learning Method for Android Malware Detection Using Various Features
inferredcites →https://doi.org/10.1109/tii.2020.2975227openalex-snapshot
Trustworthy Network Anomaly Detection Based on an Adaptive Learning Rate and Momentum in IIoT
inferredcites →https://doi.org/10.1109/trustcom/bigdatase.2019.00022openalex-snapshot
Malware Detection with Malware Images using Deep Learning Techniques
inferredcites →https://doi.org/10.1109/tst.2016.7399288openalex-snapshot
Droiddetector: android malware characterization and detection using deep learning
inferredcites →https://doi.org/10.1145/2089125.2089126openalex-snapshot
A survey on automated dynamic malware-analysis techniques and tools
inferredcites →https://doi.org/10.1145/2614628.2614633openalex-snapshot
Android taint flow analysis for app sets
inferredcites →https://doi.org/10.1145/3073559openalex-snapshot
A Survey on Malware Detection Using Data Mining Techniques
inferredcites →https://doi.org/10.1145/3366423.3380100openalex-snapshot
Directional and Explainable Serendipity Recommendation
inferredcites →https://doi.org/10.1155/2018/7247095openalex-snapshot
Detecting Malware with an Ensemble Method Based on Deep Neural Network
inferredcites →https://doi.org/10.1561/2200000006openalex-snapshot
Learning Deep Architectures for AI
inferredcites →https://doi.org/10.1609/aaai.v33i01.33019428openalex-snapshot
Anomaly Detection Using Autoencoders in High Performance Computing Systems
inferredcites →https://doi.org/10.3390/app10144966openalex-snapshot
Hybrid Malware Classification Method Using Segmentation-Based Fractal Texture Analysis and Deep Convolution Neural Network Features
inferredcites →https://doi.org/10.3390/s20247013openalex-snapshot
Deep Feature Extraction and Classification of Android Malware Images
inferredcites →https://doi.org/10.48550/arxiv.1610.05945openalex-snapshot
A multi-task learning model for malware classification with useful file access pattern from API call sequence
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4663593openalex-extracted
Fortifying Network Security with Machine Learning
inferred← citeshttps://doi.org/10.1002/cpe.7772openalex-snapshot
A robust malware traffic classifier to combat security breaches in industry 4.0 applications
inferred← citeshttps://doi.org/10.1007/978-3-031-16014-1_47openalex-snapshot
Towards Optimizing Malware Detection: An Approach Based on Generative Adversarial Networks and Transformers
inferred← citeshttps://doi.org/10.1007/978-3-031-69986-3_6openalex-snapshot
Guarding the Digital Frontier: A Logistic Regression Approach to Malware Detection
inferred← citeshttps://doi.org/10.1007/978-3-031-97632-2_2openalex-snapshot
A Robust Ensemble Malware Detector Against Powerful Adversaries
inferred← citeshttps://doi.org/10.1007/978-3-032-06078-5_8openalex-snapshot
MalGPT: A Generative Explainable Model for Malware Binaries
inferred← citeshttps://doi.org/10.1007/978-3-032-08600-6_36openalex-snapshot
AI Based Malware Detection Using Machine Learning, Random Forest, Extra Tree Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-032-22289-3_11openalex-snapshot
Advancements in Deep Learning Approaches for Malware Detection: A Comprehensive Review of Emerging Techniques
inferred← citeshttps://doi.org/10.1007/978-3-032-25080-3_20openalex-snapshot
Malware Detection in Images Using CNN
inferred← citeshttps://doi.org/10.1007/978-3-032-32476-4_49openalex-snapshot
MM-CNNRNN: An Algorithmic Framework for Multi-modal Malware Detection Integrating Binary Code and System Call Sequences
inferred← citeshttps://doi.org/10.1007/978-981-95-5082-1_17openalex-snapshot
Intelligent Co-operative Malware Detection Using Deep Learning Model
inferred← citeshttps://doi.org/10.1007/978-981-96-5010-1_6openalex-snapshot
A Novel Federated Learning Approach to Memory-Based Malware Detection Model Using RMS Propagation and Sequential Classifier
inferred← citeshttps://doi.org/10.1007/978-981-97-1249-6_11openalex-snapshot
Evaluating Different Malware Detection Neural Network Architectures
inferred← citeshttps://doi.org/10.1007/978-981-97-2447-5_10openalex-snapshot
Malware Detection System Based on Static-Dynamic Preprocessing Techniques Combined in an Ensemble Model
inferred← citeshttps://doi.org/10.1007/978-981-99-0272-9_18openalex-snapshot
Android Malware Detection: A Literature Review
inferred← citeshttps://doi.org/10.1007/978-981-99-2854-5_14openalex-snapshot
Efficient Approach for Malware Detection Using Machine Learning Classifier
inferred← citeshttps://doi.org/10.1007/s10207-026-01234-0openalex-snapshot
A hybrid machine learning intrusion detection method for metamorphic malware
inferred← citeshttps://doi.org/10.1007/s10586-024-04740-9openalex-snapshot
Botnet detection and information leakage mitigation with differential privacy under generative adversarial networks
inferred← citeshttps://doi.org/10.1007/s11416-023-00501-1openalex-snapshot
Explainable Ransomware Detection with Deep Learning Techniques
inferred← citeshttps://doi.org/10.1007/s11416-026-00597-1openalex-snapshot
A comparative study of linear and non-linear dimensionality reduction for opcode-frequency malware classification
inferred← citeshttps://doi.org/10.1007/s12083-025-02112-7openalex-snapshot
Malware Detection with AI: A Comprehensive Review of Trends and Challenges with Future Directions
inferred← citeshttps://doi.org/10.1007/s12530-022-09471-zopenalex-snapshot
DEMD-IoT: a deep ensemble model for IoT malware detection using CNNs and network traffic
inferred← citeshttps://doi.org/10.1007/s13198-024-02643-xopenalex-snapshot
A brief survey of deep learning methods for android Malware detection
inferred← citeshttps://doi.org/10.1007/s13748-025-00398-5openalex-snapshot
A transformer-based hierarchical learning model for the detection of cybersecurity threats
inferred← citeshttps://doi.org/10.1007/s13748-026-00473-5openalex-snapshot
Machine intelligence approaches for preventing adversarial malware attacks in intrusion detection systems: A systematic review
inferred← citeshttps://doi.org/10.1007/s42979-023-02404-wopenalex-snapshot
Zero-Day Malware Classification and Detection Using Machine Learning
inferred← citeshttps://doi.org/10.1007/s42979-024-03123-6openalex-snapshot
Detecting Android Malware with Convolutional Neural Networks and Hilbert Space-Filling Curves
inferred← citeshttps://doi.org/10.1016/j.aej.2025.03.118openalex-snapshot
Efficient malware detection using NLP and deep learning model
inferred← citeshttps://doi.org/10.1016/j.comnet.2026.112761openalex-snapshot
DEPN: Anti-obfuscation malware classification via dynamic manifold restoration
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2024.109139openalex-snapshot
SIM-FED: Secure IoT malware detection model with federated learning
inferred← citeshttps://doi.org/10.1016/j.cose.2024.103769openalex-snapshot
Overcoming the lack of labeled data: Training malware detection models using adversarial domain adaptation
inferred← citeshttps://doi.org/10.1016/j.cose.2025.104507openalex-snapshot
CNN-AutoMIC: Combining convolutional neural network and autoencoder to learn non-linear features for KNN-based malware image classification
inferred← citeshttps://doi.org/10.1016/j.icte.2026.01.005openalex-snapshot
Feature-driven static analysis for learning-based android malware detection: A review
inferred← citeshttps://doi.org/10.1016/j.iot.2024.101258openalex-snapshot
Image-based malware analysis for enhanced IoT security in smart cities
inferred← citeshttps://doi.org/10.1016/j.jisa.2024.103784openalex-snapshot
MalSort: Lightweight and efficient image-based malware classification using masked self-supervised framework with Swin Transformer
inferred← citeshttps://doi.org/10.1016/j.jisa.2025.104009openalex-snapshot
MA_BiRAE - Malware analysis and detection technique using adversarial learning and deep learning
inferred← citeshttps://doi.org/10.1016/j.neucom.2024.128010openalex-snapshot
A review of deep learning based malware detection techniques
inferred← citeshttps://doi.org/10.1016/j.procs.2025.03.320openalex-snapshot
A Robust Machine Learning-Based Mechanism for Detection and Analysis of Malware Attacks
inferred← citeshttps://doi.org/10.1038/s41598-026-35481-xopenalex-snapshot
Improving malware detection performance using hybrid deep representation learning with heuristic search algorithms
inferred← citeshttps://doi.org/10.1080/23737484.2026.2730597openalex-snapshot
An enhanced cybersecurity testing based on CHSPNN and DG in software testing for banking or finance applications
inferred← citeshttps://doi.org/10.1108/ijwis-03-2024-0095openalex-snapshot
A static method for detecting android malware based on directed API call
inferred← citeshttps://doi.org/10.1109/access.2023.3323396openalex-snapshot
Protecting Android Devices From Malware Attacks: A State-of-the-Art Report of Concepts, Modern Learning Models and Challenges
inferred← citeshttps://doi.org/10.1109/access.2024.3401627openalex-snapshot
TRConv: Multi-Platform Malware Classification via Target Regulated Convolutions
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.2024.3491185openalex-snapshot
Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models
inferred← citeshttps://doi.org/10.1109/access.2025.3552070openalex-snapshot
An Effective Temporal Convolutional Networks-Based Method for Detecting Android Malware Using Dynamic Extracted Features
inferred← citeshttps://doi.org/10.1109/aic61668.2024.10730896openalex-snapshot
Implementation of a Hybrid Ensemble Approach for Image-Based Malware Detection
inferred← citeshttps://doi.org/10.1109/conecct68978.2026.11700665openalex-snapshot
PermSentinel: Context-Aware Detection of Excessive Background Permission Usage in Android Applications
inferred← citeshttps://doi.org/10.1109/ibcast59916.2023.10712814openalex-snapshot
A Hybrid Framework of Meta-Learning and Generative Adversarial Networks for Few-Shot Malware Detection
inferred← citeshttps://doi.org/10.1109/icaiccit64383.2024.10912130openalex-snapshot
SeLCM: An Efficient and Robust Malware Detection Model
inferred← citeshttps://doi.org/10.1109/iccr67387.2025.11291961openalex-snapshot
The Role of Deep Learning in Modern Malware Detection: A Comparative Study of Modern Approaches
inferred← citeshttps://doi.org/10.1109/icctwc68241.2026.11583150openalex-snapshot
An Ensemble-Based Approach for Malware Detection Using Encoded Features
inferred← citeshttps://doi.org/10.1109/icdici66477.2025.11134856openalex-snapshot
Enhancing Malware Detection Using Novel Feature Encoding in Machine Learning
inferred← citeshttps://doi.org/10.1109/icdsns58469.2023.10245978openalex-snapshot
Performance Comparison of Recurrent Neural Networks for Metamorphic Malware
inferred← citeshttps://doi.org/10.1109/iceccme64568.2025.11277865openalex-snapshot
Agentic AI For Self-Evolving Malware Defense In Develops Security Automation In Battery Cell Manufacturing Driven Business
inferred← citeshttps://doi.org/10.1109/icecet63943.2025.11472357openalex-snapshot
A Novel Approach for Automated Malware Detection Using One-shot NAS and Bayesian Optimization
inferred← citeshttps://doi.org/10.1109/icesc57686.2023.10193068openalex-snapshot
Deep Learning based Malware Analysis, Prediction and Prevention
inferred← citeshttps://doi.org/10.1109/iciccs56967.2023.10142886openalex-snapshot
Prevention of Kernel Rootkit in Cloud Computing
inferred← citeshttps://doi.org/10.1109/icoco59262.2023.10397844openalex-snapshot
Dynamic Android Malware Detection Using Temporal Convolutional Networks
inferred← citeshttps://doi.org/10.1109/icoici62503.2024.10696300openalex-snapshot
Autoencoder-Driven Anomaly Detection for Efficient Malware Identification
inferred← citeshttps://doi.org/10.1109/icosci66700.2026.11448094openalex-snapshot
CAGNet - Comprehensive Node-Labeled Graph Analysis of Mobile Malware Using Force Atlas 2 and Deep Learning
inferred← citeshttps://doi.org/10.1109/icosec67334.2025.11459625openalex-snapshot
DefenSys: An Integrated Platform for Malware Detection and Containerized Attack Simulation using Deep Learning
inferred← citeshttps://doi.org/10.1109/icsecs58457.2023.10256350openalex-snapshot
CAGDEEP: Mobile Malware Analysis Using Force Atlas 2 with Strong Gravity Call Graph And Deep Learning
inferred← citeshttps://doi.org/10.1109/icsigsys67277.2025.11269166openalex-snapshot
H2O AutoML for Malware Detection: A Signal Processing Perspective on Accuracy, Efficiency, and Interpretability
inferred← citeshttps://doi.org/10.1109/icssa62312.2024.10788667openalex-snapshot
A Systematic Literature Review of Multimodal Analysis Techniques for Malware Detection
inferred← citeshttps://doi.org/10.1109/icufn57995.2023.10200885openalex-snapshot
Low-complexity Anomaly Detection Method based on Feature Importance using Shapley Value
inferred← citeshttps://doi.org/10.1109/icuis64676.2024.10867045openalex-snapshot
AG-CSE Malware Shield: Adversarial Generation and Chaotic Stacked Ensemble Approach for Deep Learning-Based Malware Classification
inferred← citeshttps://doi.org/10.1109/icwr65219.2025.11006202openalex-snapshot
Quantum Computing in Cybersecurity and LLM
inferred← citeshttps://doi.org/10.1109/iitcee59897.2024.10467722openalex-snapshot
Enhanced Malware Detection using Convolutional Neural Network with Robust Ensemble Algorithm-"LIGHTGBM"
inferred← citeshttps://doi.org/10.1109/incoft60753.2023.10425717openalex-snapshot
Multiclass Classification of Malware using Machine Learning
inferred← citeshttps://doi.org/10.1109/insect68872.2026.11663974openalex-snapshot
An Autoencoder-Enhanced Hybrid Ensemble Framework for Malware Detection
inferred← citeshttps://doi.org/10.1109/isac364032.2025.11156923openalex-snapshot
Fileless Malware Threats: Evaluating Machine Learning Algorithms for Anomaly Detection
inferred← citeshttps://doi.org/10.1109/isct62336.2024.10791190openalex-snapshot
Securing Smartphone from Mobile Phishing Attacks Using GoogLeNet Model
inferred← citeshttps://doi.org/10.1109/iske60036.2023.10481346openalex-snapshot
Efficient IoT Malware Detection Using Convolution Neural Network and View-Invariant Block
inferred← citeshttps://doi.org/10.1109/ispcc66872.2025.11039576openalex-snapshot
Machine Learning-Driven Android Malware Detection: A Robust Approach
inferred← citeshttps://doi.org/10.1109/itt69610.2025.11352918openalex-snapshot
A Novel Artificial Intelligence Driven Dynamic Adaptive Temporal Deep Learning Framework for Dynamic Malware Detection
inferred← citeshttps://doi.org/10.1109/jiot.2026.3682602openalex-snapshot
Optimizing Network Security in IoT Networks: Leveraging Graph Learning for Zero-Trust Authentication
inferred← citeshttps://doi.org/10.1109/netact65906.2025.11187442openalex-snapshot
Detection of Malware on Portable Executable Files Using Machine Learning
inferred← citeshttps://doi.org/10.1109/picc57976.2023.10142498openalex-snapshot
Architectural Design of Malware Infected File Detection Using Deep Learning
inferred← citeshttps://doi.org/10.1109/southeastcon52093.2024.10500127openalex-snapshot
Effectiveness of Image-Based Deep Learning on Token-Level Software Vulnerability Detection
inferred← citeshttps://doi.org/10.1109/spicscon69221.2025.11504245openalex-snapshot
Deep Autoencoder-Based Protection for Malware Detection Models from Adversarially Perturbed Data
inferred← citeshttps://doi.org/10.1109/tensymp61132.2024.10752108openalex-snapshot
Enhancing Malware Detection Through Convolutional Neural Networks and Explainable AI
inferred← citeshttps://doi.org/10.1109/tifs.2024.3350379openalex-snapshot
Static Multi Feature-Based Malware Detection Using Multi SPP-net in Smart IoT Environments
inferred← citeshttps://doi.org/10.1109/worldsuas66815.2025.11198951openalex-snapshot
Performance Analysis for Advancement in Machine Learning to Detect Dynamic Malware in MANET
inferred← citeshttps://doi.org/10.1111/1556-4029.70189openalex-snapshot
Enhancing malware detection and classification in network traffic using deep learning techniques
inferred← citeshttps://doi.org/10.1145/3638240openalex-snapshot
A Survey of Recent Advances in Deep Learning Models for Detecting Malware in Desktop and Mobile Platforms
inferred← citeshttps://doi.org/10.1155/2022/2959222openalex-snapshot
Deep Learning Methods for Malware and Intrusion Detection: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1186/s13677-023-00549-wopenalex-snapshot
Volatile Kernel Rootkit hidden process detection in cloud computing
inferred← citeshttps://doi.org/10.17762/ijritcc.v11i9.9581openalex-snapshot
IoT malware detection using a novel 3-Sigma Auto-Funnel Transformer approach
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2780527/v1openalex-snapshot
Comprehensive Analysis of Android Malware detection through Semi-supervised Autoencoder models
inferred← citeshttps://doi.org/10.21203/rs.3.rs-6615092/v1openalex-snapshot
SmartGuard: An Adaptive Hybrid Malware Detection Framework for IoT Systems Using Multi- Stream Deep Learning and Dynamic Feedback Optimization
inferred← citeshttps://doi.org/10.2339/politeknik.1536669openalex-snapshot
Efficientnet-Based Deep Learning for Malware Classification: A Dynamic Distribution Adaptation Approach
inferred← citeshttps://doi.org/10.31144/si.2307-6410.2024.n24.p113-122openalex-snapshot
ВЫЯВЛЕНИЕ ВРЕДОНОСНЫХ ШАБЛОНОВ: ОБНАРУЖЕНИЕ ВРЕДОНОСНЫХ ПРОГРАММ НА ОСНОВЕ АВТОЭНКОДЕРА
inferred← citeshttps://doi.org/10.32604/cmc.2024.057234openalex-snapshot
AI-Driven Prioritization and Filtering of Windows Artifacts for Enhanced Digital Forensics
inferred← citeshttps://doi.org/10.32604/cmc.2025.066551openalex-snapshot
A Novel Malware Detection Framework for Internet of Things Applications
inferred← citeshttps://doi.org/10.3390/ecsa-10-16234openalex-snapshot
Enhancing Insider Malware Detection Accuracy with Machine Learning Algorithms
inferred← citeshttps://doi.org/10.3390/electronics14132741openalex-snapshot
An Efficient Malware Detection Method Using a Hybrid ResNet-Transformer Network and IGOA-Based Wrapper Feature Selection
inferred← citeshttps://doi.org/10.3390/fi17120554openalex-snapshot
MalScore: A Quality Assessment Framework for Visual Malware Datasets Using No-Reference Image Quality Metrics
inferred← citeshttps://doi.org/10.3390/info17070643openalex-snapshot
A Lightweight Framework for Android Malware Detection via SDAE-Based Multi-View Static Feature Fusion
inferred← citeshttps://doi.org/10.3390/jcp6050148openalex-snapshot
Empirical Evaluation and New Insights of Concept Drift in ML-Based Android Malware Detection
inferred← citeshttps://doi.org/10.35377/saucis...1341082openalex-snapshot
Classification of Malware Images Using Fine-Tunned ViT
inferred← citeshttps://doi.org/10.3934/math.2024739openalex-snapshot
Leveraging deep learning and image conversion of executable files for effective malware detection: A static malware analysis approach
inferred← citeshttps://doi.org/10.4018/979-8-3693-8944-7.ch011openalex-snapshot
A New Approach for Detecting Malware Using a Convolutional Autoencoder With Kernel Density Estimation
inferred← citeshttps://doi.org/10.4018/ijiit.329956openalex-snapshot
Android Malware Detection Approach Using Stacked AutoEncoder and Convolutional Neural Networks
inferred← citeshttps://doi.org/10.4274/eajem.galenos.2025.80688openalex-snapshot
Association between Inflammatory Markers Measured at Emergency Admission and In-Hospital Mortality Among Patients with Acute Ischemic Stroke
inferred← citeshttps://doi.org/10.4274/tjd.galenos.2024.60362openalex-snapshot
Review of Treatment Algorithms in Mycosis Fungoides and Sezary Syndrome
inferred← citeshttps://doi.org/10.7717/peerj-cs.3408openalex-snapshot
Semantic-aware framework for zero-shot malware classification via attention-based relation network
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.