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AI for Cybersecurity: Robust models for Authentication, Threat and Anomaly Detection

Resumen/Descripción – provisto por la editorial

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Palabras clave – provistas por la editorial

Internet of Things; cybersecurity; cyber threats; malware detection; machine learning; network traffic; cooperative intelligent transportation systems (cITSs); IDS; vehicular ad-hoc networks (VANET); adaptive model; deep belief network (DBN); NIDS; deep learning; false negative rate; artificial neural network; MITRE ATT&CK Matrix; techniques classification; BERT-based multi-labeling; formal ontology; risk identification; vulnerability; portable executable malware; tree-based ensemble; performance comparison; statistical significance test; adversarial examples; face recognition; mask matrix; targeted attack; non-targeted attack; anomaly detection; attack detection; cyber-physical system; datasets; evaluation metrics; biometric cryptosystem; iris identification; error-correcting codes; intrusion detection; smart grid; neural networks; n/a