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Securing IoT Devices Running PureOS from Ransomware Attacks: Leveraging Hybrid Machine Learning Techniques

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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.

1 of the 33 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1520/jte20220100 (notice 2026-01-26).

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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/spe.2420openalex-snapshot
CloudEyes: Cloud‐based malware detection with reversible sketch for resource‐constrained internet of things (IoT) devices
inferredcites →https://doi.org/10.1007/s10207-022-00602-wopenalex-snapshot
Intelligent and behavioral-based detection of malware in IoT spectrum sensors
inferredcites →https://doi.org/10.1007/s11416-015-0252-0openalex-snapshot
Support vector machines and malware detection
inferredcites →https://doi.org/10.1007/s11416-019-00338-7openalex-snapshot
A Cyber-Kill-Chain based taxonomy of crypto-ransomware features
inferredcites →https://doi.org/10.1016/j.anucene.2021.108725openalex-snapshot
Development of a cyberattack response planning method for nuclear power plants by using the Markov decision process model
inferredcites →https://doi.org/10.1016/j.compeleceng.2022.107903openalex-snapshot
Mitigating adversarial evasion attacks of ransomware using ensemble learning
inferredcites →https://doi.org/10.1016/j.cose.2023.103177openalex-snapshot
RecMaL: Rectify the malware family label via hybrid analysis
inferredcites →https://doi.org/10.1016/j.enbenv.2021.01.009openalex-snapshot
Trends, benefits, risks, and challenges of IoT implementation in residential and commercial buildings
inferredcites →https://doi.org/10.1016/j.eswa.2021.116198openalex-snapshot
The rise of ransomware: Forensic analysis for windows based ransomware attacks
inferredcites →https://doi.org/10.1016/j.icte.2021.08.005openalex-snapshot
Compact feature hashing for machine learning based malware detection
inferredcites →https://doi.org/10.1016/j.measen.2022.100654openalex-snapshot
ENetRM: ElasticNet Regression Model based malicious cyber-attacks prediction in real-time server
inferredcites →https://doi.org/10.1016/s1361-3723(20)30082-8openalex-snapshot
ESET: Threat Report Q2 2020
inferredcites →https://doi.org/10.1038/s41746-019-0161-6openalex-snapshot
A retrospective impact analysis of the WannaCry cyberattack on the NHS
inferredcites →https://doi.org/10.1109/access.2022.3146363openalex-snapshot
LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
inferredcites →https://doi.org/10.1109/access.2022.3171912openalex-snapshot
Malware Detection Using LightGBM With a Custom Logistic Loss Function
inferredcites →https://doi.org/10.1109/ccaa.2016.7813706openalex-snapshot
Cyber ethics and cyber crime: A deep dwelved study into legality, ransomware, underground web and bitcoin wallet
inferredcites →https://doi.org/10.1109/icefeet51821.2022.9848192openalex-snapshot
Performance Enhancement of SVM-based ML Malware Detection Model Using Data Preprocessing
inferredcites →https://doi.org/10.1109/icpads56603.2022.00061openalex-snapshot
OutletGuarder: Detecting DarkSide Ransomware by Power Factor Correction Signals in an Electrical Outlet
inferredcites →https://doi.org/10.1109/mobisecserv.2017.7886569openalex-snapshot
Knowing the ransomware and building defense against it - specific to healthcare institutes
inferredcites →https://doi.org/10.1109/msp.2018.2701165openalex-snapshot
Protecting against Ransomware: A New Line of Research or Restating Classic Ideas?
inferredcites →https://doi.org/10.1177/20438869221110246openalex-snapshot
From disruption to ransomware: Lessons From hackers
inferredcites →https://doi.org/10.1186/s40163-019-0097-9openalex-snapshot
Ransomware deployment methods and analysis: views from a predictive model and human responses
inferredcites →https://doi.org/10.14421/ijid.2021.2423openalex-snapshot
Analysis of Conti Ransomware Attack on Computer Network with Live Forensic Method
inferredcites →https://doi.org/10.1520/jte20220100openalex-snapshot
RETRACTED: Malware Detection Algorithm for Wireless Sensor Networks in a Smart City Based on Random Forest
inferredcites →https://doi.org/10.2139/ssrn.4358561openalex-snapshot
Blockchain Forensics and Crypto-Related Cybercrimes
inferredcites →https://doi.org/10.22219/repositor.v4i1.1373openalex-snapshot
Analisis Ransomware Wannacry Menggunakan Aplikasi Cuckoo Sandbox
inferredcites →https://doi.org/10.23940/ijpe.18.03.p15.547558openalex-snapshot
Andro_MD: Android Malware Detection based on Convolutional Neural Networks
inferredcites →https://doi.org/10.31154/cogito.v8i1.356.232-243openalex-snapshot
LockBit 2.0 Ransomware: Analysis of infection, persistence, prevention mechanism
inferredcites →https://doi.org/10.3390/app12136672openalex-snapshot
MLMD—A Malware-Detecting Antivirus Tool Based on the XGBoost Machine Learning Algorithm
inferredcites →https://doi.org/10.3390/electronics11193142openalex-snapshot
PDF Malware Detection Based on Optimizable Decision Trees
inferredcites →https://doi.org/10.3390/electronics12040789openalex-snapshot
NT-GNN: Network Traffic Graph for 5G Mobile IoT Android Malware Detection
inferredcites →https://doi.org/10.3390/math11010249openalex-snapshot
Retaliation against Ransomware in Cloud-Enabled PureOS System
inferredcites →https://doi.org/10.34028/iajit/19/2/13openalex-snapshot
Multichannel Based IoT Malware Detection System Using System Calls and Opcode Sequences

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-981-96-3936-6_27openalex-snapshot
Ransomware Detection on Windows Systems
inferred← citeshttps://doi.org/10.1007/s10207-024-00930-zopenalex-snapshot
IoT device security audit tools: a comprehensive analysis and a layered architecture approach for addressing expanded security requirements
inferred← citeshttps://doi.org/10.1007/s42979-025-03765-0openalex-snapshot
Exploring the Landscape of IoT Ransomware Prediction Through Machine Learning Techniques: A Comprehensive Survey
inferred← citeshttps://doi.org/10.1016/b978-0-44-322217-7.00015-3openalex-snapshot
IoT cloud security in digital transformation
inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e29917openalex-snapshot
Combatting ransomware in ZephyrOS-activated industrial IoT environments
inferred← citeshttps://doi.org/10.1038/s41598-025-23899-8openalex-snapshot
Mitigating distributed denial of service-based cyberattack in federated computing framework using deep reinforcement learning with frilled lizard algorithm
inferred← citeshttps://doi.org/10.1109/etfa61755.2024.10710882openalex-snapshot
Towards Unveiling Vulnerabilities and Securing IoT Devices: An Ontology-Based Approach
inferred← citeshttps://doi.org/10.1109/icpct64145.2025.10941048openalex-snapshot
Smart City Cybersecurity: Leveraging Machine Learning for Advanced Ransomware Detection and Prevention
inferred← citeshttps://doi.org/10.1109/wids-psu61003.2024.00046openalex-snapshot
Ransomware Detection in the Internet of Things (IoT): Challenges and Emerging Solutions
inferred← citeshttps://doi.org/10.11591/ijece.v14i4.pp4664-4674openalex-snapshot
Insights of machine learning-based threat identification schemes in advanced network system
inferred← citeshttps://doi.org/10.11591/ijeecs.v34.i2.pp970-982openalex-snapshot
Proactive ransomware prevention in pervasive IoMT via hybrid machine learning
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3689581/v1openalex-snapshot
LLaMa Assisted Reverse Engineering of Modern Ransomware: A Comparative Analysis with Early Crypto-Ransomware
inferred← citeshttps://doi.org/10.3390/electronics12183899openalex-snapshot
Enhancing Ransomware Attack Detection Using Transfer Learning and Deep Learning Ensemble Models on Cloud-Encrypted Data
inferred← citeshttps://doi.org/10.3390/math11163552openalex-snapshot
P4-HLDMC: A Novel Framework for DDoS and ARP Attack Detection and Mitigation in SD-IoT Networks Using Machine Learning, Stateful P4, and Distributed Multi-Controller Architecture
inferred← citeshttps://doi.org/10.47392/irjaem.2024.0079openalex-snapshot
Comprehensive Swotting on Librem 5
inferred← citeshttps://doi.org/10.63313/cs.8015openalex-snapshot
PrimLock: Leveraging Linear Programming to Optimize Primitive Logic Locking
inferred← citeshttps://doi.org/10.70389/pjs.100038openalex-snapshot
Cybersecurity in the Era of IoT: A Review of Vulnerabilities, Threats, and Mitigation Strategies
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