Delegated Autonomy, Real Security: Authorization for AI Agents in IoT & Multi‑Agent Systems

Autonomous AI agents are quickly moving from nice-to-have assistants to real actors in the world. They can book travel, manage accounts, coordinate workflows, and interact directly with IoT devices and edge services in real time. That shift raises a tough security question: how do we delegate authority to an AI agent in a way thats explicit and transparent, keeps humans in control, and still stays lightweight and privacy-preserving?

This project targets a clear gap. Most Identity and Access Management (IAM) systems were built for long-lived users and stable services. They werent designed for AI agents that might exist only for a single task, use multiple tools, and make decisions based on context. In practice, agents can appear briefly and vanish once the job is done, jump across different tools and organisations to complete a workflow, collaborate with other agents in multi-agent settings, and operate at the edge where compute is limited and connectivity can be unreliable.

Research on agentic authorization keeps running into the same issues: delegation across multiple entities is clunky, context is hard to capture and enforce, and token or session management doesnt scale well when hundreds or thousands of agents interact with many services and devices.

Your role in this project is to help design and prototype principled access-control mechanisms tailored for delegated AI agents at the edge. The goal is to give people clear, meaningful control over permissions, identity, and accountability, while ensuring the system can reliably enforce those choices. Youll be working with a research team developing innovative solutions in this space.