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Cross-Method-Based Analysis and Classification of Malicious Behavior by API Calls Extraction
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cpe.4172openalex-snapshot
Detection of malicious behavior in android apps through API calls and permission uses analysis
inferredcites →https://doi.org/10.1007/978-1-4471-2909-7openalex-snapshot
Software Similarity and Classification
inferredcites →https://doi.org/10.1007/978-3-319-25512-5_2openalex-snapshot
Development and Initial User Evaluation of a Virtual Crime Scene Simulator Including Digital Evidence
inferredcites →https://doi.org/10.1007/978-3-642-37832-4_21openalex-snapshot
CBM: Free, Automatic Malware Analysis Framework Using API Call Sequences
inferredcites →https://doi.org/10.1007/s10207-014-0233-1openalex-snapshot
A defense framework against malware and vulnerability exploits
inferredcites →https://doi.org/10.1007/s10844-010-0148-xopenalex-snapshot
“Andromaly”: a behavioral malware detection framework for android devices
inferredcites →https://doi.org/10.1016/j.cose.2018.04.005openalex-snapshot
Malware identification using visualization images and deep learning
inferredcites →https://doi.org/10.1016/j.diin.2016.04.006openalex-snapshot
Anti-forensics: Furthering digital forensic science through a new extended, granular taxonomy
inferredcites →https://doi.org/10.1016/j.neucom.2014.08.060openalex-snapshot
Dynamical analysis and optimal control for a malware propagation model in an information network
inferredcites →https://doi.org/10.1016/j.physa.2018.05.047openalex-snapshot
Modeling and analyzing malware propagation in social networks with heterogeneous infection rates
inferredcites →https://doi.org/10.1016/j.procs.2016.03.084openalex-snapshot
Trust-based Voting Method for Efficient Malware Detection
inferredcites →https://doi.org/10.1109/glocom.2016.7841778openalex-snapshot
Efficient Dynamic Malware Analysis Based on Network Behavior Using Deep Learning
inferredcites →https://doi.org/10.1109/iceei.2015.7352513openalex-snapshot
Malware detection on Android smartphones using API class and machine learning
inferredcites →https://doi.org/10.1109/malware.2010.5665796openalex-snapshot
Differentiating malware from cleanware using behavioural analysis
inferredcites →https://doi.org/10.1109/tase.2014.2348555openalex-snapshot
An Incremental-and-Static-Combined Scheme for Matrix-Factorization-Based Collaborative Filtering
inferredcites →https://doi.org/10.1109/tdsc.2006.41openalex-snapshot
System Call Monitoring Using Authenticated System Calls
inferredcites →https://doi.org/10.1109/tdsc.2013.40openalex-snapshot
Control Flow-Based Malware VariantDetection
inferredcites →https://doi.org/10.1109/tmi.2014.2305394openalex-snapshot
Image-Based Quantitative Analysis of Gold Immunochromatographic Strip via Cellular Neural Network Approach
inferredcites →https://doi.org/10.1109/wimob.2014.6962194openalex-snapshot
Investigating the android intents and permissions for malware detection
inferredcites →https://doi.org/10.1145/1774088.1774303openalex-snapshot
Malware detection based on mining API calls
inferredcites →https://doi.org/10.1145/948187.948201openalex-snapshot
Detection of injected, dynamically generated, and obfuscated malicious code
inferredcites →https://doi.org/10.1186/s40064-016-1861-xopenalex-snapshot
Detecting and classifying method based on similarity matching of Android malware behavior with profile
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Identifying False Alarm for Network Intrusion Detection System Using Hybrid Data Mining and Decision Tree
inferredcites →https://doi.org/10.3390/app8071044openalex-snapshot
HM3alD: Polymorphic Malware Detection Using Program Behavior-Aware Hidden Markov Model
inferredcites →https://doi.org/10.3390/app8091622openalex-snapshot
Web-Based Android Malicious Software Detection and Classification System
inferredcites →https://doi.org/10.3390/e17042367openalex-snapshot
An Entropy-Based Network Anomaly Detection Method
inferredcites →https://doi.org/10.3390/su9020262openalex-snapshot
Practical In-Depth Analysis of IDS Alerts for Tracing and Identifying Potential Attackers on Darknet
inferredcites →https://doi.org/10.3390/sym9040049openalex-snapshot
Methods and Tools of Digital Triage in Forensic Context: Survey and Future Directions
inferredcites →https://doi.org/10.48550/arxiv.1104.3228openalex-snapshot
Metamorphic Virus Variants Classification Using Opcode Frequency Histogram
inferredcites →https://doi.org/10.5121/ijnsa.2014.6101openalex-snapshot
Optimised Malware Detection in Digital Forensics
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Malware Detected and Tell Me Why: An Verifiable Malware Detection Model with Graph Metric Learning
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inferred← citeshttps://doi.org/10.1016/j.eswa.2026.131781openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.infsof.2020.106273openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.infsof.2026.108241openalex-snapshot
API2TA: Learning tactic-aware representations of APIs for malware detection, classification and understanding
inferred← citeshttps://doi.org/10.1016/j.jisa.2025.104104openalex-snapshot
FETA: A systematic and efficient approach for feature engineering on anti-static and anti-dynamic malware analysis
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SaBER-LLMs: Security-aware behavior embedding representation via large language models for fine-grained malware analysis
inferred← citeshttps://doi.org/10.1016/j.sysarc.2020.101861openalex-snapshot
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Reliability and Optimum Cost Analysis of Malware Infected System by Discrete-Time Negative Arrival Retrial Queue
inferred← citeshttps://doi.org/10.1080/1206212x.2020.1732641openalex-snapshot
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Malware Detection Issues, Future Trends and Challenges: A Survey
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PlausMal-GAN: Plausible Malware Training Based on Generative Adversarial Networks for Analogous Zero-Day Malware Detection
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Malicious Behavior Detection based on Extracted Features from APIs for Windows Platforms
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