Architecting secure Smart infrastructures with AI microservices and autonomous agents: A State-of-the-Art review and healthcare use case

Abstract

Cyber threats in smart infrastructure, including industrial IoT, healthcare systems, and cloud-edge environments, have evolved and call for smart security systems combining artificial intelligence microservices with autonomous agents. Traditional methods lack the flexibility required for proactive and cross-sector defense. This paper looks at state-of-the-art AI-powered microservices (e.g., NVIDIA, AWS, Azure, Google) and their integration with autonomous agents for adaptive governance, threat mitigation, and anomaly detection. A reference architecture is suggested to support interoperability, federated learning, and resilience after quantum computing. Through a healthcare use case we show how secure data exchange, predictive diagnostics, and compliance enforcement can be used in areas like digital heritage protection, precision agriculture, and supply chain security. Our study gives us useful information for making AI-driven infrastructures that are safe, scalable, and long-lasting.