AI + IoT Security: Safeguarding Smart Devices
Edge intelligence, anomaly detection at device level, and privacy-aware IoT monitoring.
Edge intelligence, anomaly detection at device level, and privacy-aware IoT monitoring.
Federated learning, homomorphic encryption, and secure multiparty computation applied to security.
Comparative criteria, integration tips, and evaluation metrics for TIPs.
Prompt injection, model poisoning, and defensive prompt engineering.
Capabilities, false positive risks, and explainability limits for zero-day detection.
Career pathways, skill recommendations, and certification suggestions.
Adaptive authentication, risk-based access, and continuous verification.
Data validation, provenance, and robust aggregation as defenses.
Trends at the intersection of quantum-safe cryptography, AI, and autonomous defense.
GAN use-cases for synthetic data generation and adversarial testing.