Dynamic weight clustered federated learning for IoT DDoS attack detection. [PDF]
Beshah YK, Abebe SL, Melaku HM.
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Optimized ensemble machine learning model for cyberattack classification in industrial IoT. [PDF]
Alabdullah B, Sankaranarayanan S.
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Designing a neuro-symbolic dual-model architecture for explainable and resilient intrusion detection in IoT networks. [PDF]
Almadhor A +5 more
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A deep reinforcement based echo state network for network intrusion classification. [PDF]
Alam K, Bhuiyan MH, Farid DM.
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Enhancing SDN security with deep learning and F-balanced cross-entropy for DDoS detection. [PDF]
Naeen HM, Ghadamyari M, Barmar M.
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Correction: Okey et al. BoostedEnML: Efficient Technique for Detecting Cyberattacks in IoT Systems Using Boosted Ensemble Machine Learning. <i>Sensors</i> 2022, <i>22</i>, 7409. [PDF]
Okey OD +6 more
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Smart IoT applications of multi attack detection using cluster F1MI approach. [PDF]
Nagavel V, Bhuvaneswari PTV, Ramesh P.
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Advancements in cyberthreat intelligence through resource exhaustion attack detection using hybrid deep learning with heuristic search algorithms. [PDF]
Jayanthi S +6 more
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A hybrid deep learning model for detection and mitigation of DDoS attacks in VANETs. [PDF]
Jayakrishna N, Prasanth NN.
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DDoS attack detection in Edge-IIoT digital twin environment using deep learning approach. [PDF]
Al-Obeidat F +3 more
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