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Blockchain and explainable AI for enhanced decision making in cyber threat detection

https://doi.org/10.1002/spe.3319
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What this work says

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

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A federated learning method for network intrusion detection
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A Blockchain‐based Cyber Attack Detection Scheme for Decentralized Internet of Things using Software‐Defined Network
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Android malware detection using network traffic based on sequential deep learning models
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DDoS attack detection in smart home applications
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Automated detection of cybersecurity attacks in healthcare systems with recursive feature elimination and multilayer perceptron optimization
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An ensemble learning and fog-cloud architecture-driven cyber-attack detection framework for IoMT networks
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A Multi-View attention-based deep learning framework for malware detection in smart healthcare systems
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A comprehensive study of DDoS attacks over IoT network and their countermeasures
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Transparency and accountability in AI decision support: Explaining and visualizing convolutional neural networks for text information
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Incorporating FAT and privacy aware AI modeling approaches into business decision making frameworks
inferredcites →https://doi.org/10.1016/j.future.2018.03.054openalex-snapshot
Edge cognitive computing based smart healthcare system
inferredcites →https://doi.org/10.1016/j.future.2021.09.010openalex-snapshot
XSRU-IoMT: Explainable simple recurrent units for threat detection in Internet of Medical Things networks
inferredcites →https://doi.org/10.1016/j.ijhcs.2020.102551openalex-snapshot
The effects of explainability and causability on perception, trust, and acceptance: Implications for explainable AI
inferredcites →https://doi.org/10.1016/j.ins.2023.119000openalex-snapshot
An explainable deep learning-enabled intrusion detection framework in IoT networks
inferredcites →https://doi.org/10.1016/j.scs.2021.102994openalex-snapshot
A new distributed architecture for evaluating AI-based security systems at the edge: Network TON_IoT datasets
inferredcites →https://doi.org/10.1109/access.2020.2988359openalex-snapshot
An Explainable Machine Learning Framework for Intrusion Detection Systems
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Multi-Head Self-Attention-Based Deep Clustering for Single-Channel Speech Separation
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Secure Industrial IoT Systems via RF Fingerprinting Under Impaired Channels With Interference and Noise
inferredcites →https://doi.org/10.1109/cict56698.2022.9997815openalex-snapshot
Efficient Mutual Authentication Scheme for IoT-based Healthcare System
inferredcites →https://doi.org/10.1109/comst.2022.3158270openalex-snapshot
A Survey of Intelligent Network Slicing Management for Industrial IoT: Integrated Approaches for Smart Transportation, Smart Energy, and Smart Factory
inferredcites →https://doi.org/10.1109/icgtspicc.2016.7955360openalex-snapshot
A model for smart agriculture using IoT
inferredcites →https://doi.org/10.1109/jbhi.2021.3101686openalex-snapshot
An Intrusion Detection Mechanism for Secured IoMT Framework Based on Swarm-Neural Network
inferredcites →https://doi.org/10.1109/jbhi.2022.3186250openalex-snapshot
Dew-Cloud-Based Hierarchical Federated Learning for Intrusion Detection in IoMT
inferredcites →https://doi.org/10.1109/jiot.2020.2996590openalex-snapshot
A Deep Blockchain Framework-Enabled Collaborative Intrusion Detection for Protecting IoT and Cloud Networks
inferredcites →https://doi.org/10.1109/jiot.2021.3130156openalex-snapshot
A New Explainable Deep Learning Framework for Cyber Threat Discovery in Industrial IoT Networks
inferredcites →https://doi.org/10.1109/jiot.2023.3234530openalex-snapshot
OPTIMIST: Lightweight and Transparent IDS With Optimum Placement Strategy to Mitigate Mixed-Rate DDoS Attacks in IoT Networks
inferredcites →https://doi.org/10.1109/mce.2022.3164529openalex-snapshot
Securing Clustered Edge Intelligence With Blockchain
inferredcites →https://doi.org/10.1109/tce.2023.3277856openalex-snapshot
An Intelligent Intrusion Detection System for Smart Consumer Electronics Network
inferredcites →https://doi.org/10.1109/tce.2023.3283704openalex-snapshot
An Explainable and Resilient Intrusion Detection System for Industry 5.0
inferredcites →https://doi.org/10.1109/tii.2022.3181614openalex-snapshot
ANAF-IoMT: A Novel Architectural Framework for IoMT-Enabled Smart Healthcare System by Enhancing Security Based on RECC-VC
inferredcites →https://doi.org/10.1109/tits.2020.2986697openalex-snapshot
Detecting Driver Behavior Using Stacked Long Short Term Memory Network With Attention Layer
inferredcites →https://doi.org/10.1109/tits.2022.3188671openalex-snapshot
An Explainable Deep Learning Framework for Resilient Intrusion Detection in IoT-Enabled Transportation Networks
inferredcites →https://doi.org/10.1109/tkde.2022.3187013openalex-snapshot
A Survey on Dropout Methods and Experimental Verification in Recommendation
inferredcites →https://doi.org/10.1109/tla.2022.9662173openalex-snapshot
Internet of Things: State-of-the-art, Computing Paradigms and Reference Architectures
inferredcites →https://doi.org/10.3390/electronics10121375openalex-snapshot
Security of Things Intrusion Detection System for Smart Healthcare
inferredcites →https://doi.org/10.3390/electronics11193079openalex-snapshot
Explainable Artificial Intelligence for Intrusion Detection System
inferredcites →https://doi.org/10.3390/s21093025openalex-snapshot
A Framework for Malicious Traffic Detection in IoT Healthcare Environment
inferredcites →https://doi.org/10.3917/ennu.012.0031openalex-snapshot
A Note on the Interpretability of Machine Learning Algorithms

What points at this work

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

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inferred← citeshttps://doi.org/10.1007/s41870-025-02466-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114402openalex-snapshot
Blockchain-assisted explainable decision traces (BAXDT): An approach for transparency and accountability in artificial intelligence systems
inferred← citeshttps://doi.org/10.1016/j.pmcj.2025.102123openalex-snapshot
XAI-driven multi-attention DeepCRNN for enhanced cyberattack detection in internet of medical things environments
inferred← citeshttps://doi.org/10.1016/j.procs.2026.06.392openalex-snapshot
Adaptive Feature-Enhanced CNN-BiLSTM Architecture for Network Intrusion Detection: A Multi-Stage Learning Approach with Interpretable Deep Analysis
inferred← citeshttps://doi.org/10.1038/s41598-025-15146-xopenalex-snapshot
Explainable artificial intelligence-based cyber resilience in internet of things networks using hybrid deep learning with improved chimp optimization algorithm
inferred← citeshttps://doi.org/10.1038/s41598-025-27515-7openalex-snapshot
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A Comprehensive Survey of Explainable Artificial Intelligence Techniques for Malicious Insider Threat Detection
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Hybrid Transformer–CNN Neuro-Symbolic Explainable AI for Cyber Threat Intelligence: Advancing Transparency and Adversarial Robustness
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