Systematic Evaluation of Machine Learning and Deep Learning Models for IoT Malware Detection Across Ransomware, Rootkit, Spyware, Trojan, Botnet, Worm, Virus, and Keylogger. [PDF]
Sensors (Basel)Maghanaki M +3 more
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Hyperparameter optimization of XGBoost and hybrid CnnSVM for cyber threat detection using modified Harris hawks algorithm. [PDF]
PeerJ Comput SciElwahsh H +7 more
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Self-Organizing Neural Grove for Malware Detection in IoT Edge Devices. [PDF]
Sensors (Basel)Inoue H, Komura T, Hashimoto I.
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Generative Adversarial Networks for Intrusion Detection Systems: A Comprehensive Survey of Applications, Challenges, and Research Directions. [PDF]
Arab J Sci EngAlauthman M +4 more
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A Novel Architecture for Mitigating Botnet Threats in AI-Powered IoT Environments. [PDF]
Sensors (Basel)Memos VA +4 more
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An efficient data driven framework for intrusion detection in wireless sensor networks using deep learning. [PDF]
Sci RepSinha P +6 more
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Evaluation of Explainable Artificial Intelligence in IoT Intrusion Detection Systems Under DeepFool Adversarial Conditions. [PDF]
Sensors (Basel)Munilla J, Khammas RM.
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Fed-DTCN: A Federated Disentangled Learning Framework for Unsupervised Zero-Day Anomaly Detection in IoT with Semantic-Aware Augmentation. [PDF]
Sensors (Basel)Khan MA, Khalid O, Rais RNB.
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Combination of quantum-based optimizer and feature pyramid network for intrusion detection in Cloud-IoT environments. [PDF]
Sci RepHajlaoui R +3 more
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A privacy preserving intrusion detection framework for IIoT in 6G networks using homomorphic encryption and graph neural networks. [PDF]
Sci RepHua B, Xi H.
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