Every team ARIA funds through Scaling Trust, placed on our working map of the stack. The map grows as new teams join each quarter.
12 teams · 3 tracks · updated 7 October 2026
Arena partners
Environment & challenge design
Physical build & operations
Security & red teaming
Community partners
Industry partners
Digital partners
Open-source practice, use cases
Digital stack
Agents · agentic loop
Agents · new models
Agents · negotiation
Tools · TEE sandbox, auditing
Integration
Glues the stack together
Physical stack
Physical verification · bridges, sensors, actuators
Physical environments · evals, benchmarks, harness
Cyber-physical partners
Real-world data and environments
Theory of secure agent interaction
Generative security
Formal AI security
Secure agent interaction
Cyber-physical bridges
Physical verification theory
Secure hardware
Nature cryptography
Physical environments · evals, world models
An agentic security stack that captures security and privacy risks, requirements and functionality boundaries, translates task requirements into formal specifications, selects or generates suitable cryptographic protocols (e.g. secure comms, MPC, ZK), and verifies their properties with Lean, ProVerif and similar tools. The goal is an end-to-end workflow in which agents, from orchestrators to sub-agents, can negotiate security needs and connect verified protocol descriptions to executable multi-agent interactions.
Team: Myrto Arapinis, Jianyi Cheng, Michele Ciampi, Wenda Li (University of Edinburgh)
Privacy techniques suited to AI workloads, built with cryptography: private retrieval for RAG, semantic search, secure computation, and methods for concealing queries or embeddings. The aim is to let agents use shared memory and sensitive data without exposing commercially or personally confidential information.
Team: Nir Bitansky (NYU); Yuval Ishai (Technion); Ron Rothblum (Succinct/Technion); Sarah Meiklejohn (UCL/Google)
An automated mechanism and protocol design engine. Agents specify desired properties, such as incentive compatibility, safety and liveness, and Dovetail designs an interaction protocol and proves in Lean that it satisfies those requirements. The team will also manage a cross-team repository of protocols, with the goal of speeding up automated protocol generation.
Team: Emanuele La Malfa, Angelo Huang (Institute for Decentralized AI); Mirco Giacobbe, Gabriel Santos (Zeroth Research)
ProtoSage is an agentic system for auditing cryptographic protocols, supported by ProtoBench’s corpus and evaluation tasks. The project builds on OpenSage and WireWatch to identify vulnerabilities, recover protocol specifications, and eventually produce machine-checkable models that experts and formal-verification tools can inspect.
Team: Mona Wang (RDI Foundation)
Enables mutually untrusting AI agents, for example representing different companies, to establish trust by cryptographically proving facts about those companies and their physical-world processes to each other: that a product was produced to a particular specification, say, or under what conditions an agent would be willing to reach an agreement.
CCTI is also the programme’s integration partner, mapping how Creators’ work fits together, co-developing shared building blocks with interested teams, and proposing open-source benchmarks and challenges to the Arena.
Team: grjte (Ink & Switch); Hossein Hafezi, Alireza Kavousi, Arman Kolozyan, Jessica Man (University of Cambridge); Jonathan Heiß, Ágnes Kiss, Aurel Stenzel (SINE); Daniel Hugenroth, Mario Lins (Light Squares)
A tamper-resistant physical watermarking framework to verify the provenance and safety compliance of control policies driving embodied robots. By extending the Colored Noise Coherency (CoNoCo) construction, it lets independent parties remotely authenticate active controllers using commodity hardware, such as standard CCTV cameras or smartphones, without direct access to the robot or specialised sensing equipment.
Team: Manon Flageat, Mateusz Sypniewski, Sally Matthews (University of Cambridge)
Connects the programme to practical industrial needs. Drawing on its manufacturing expertise, the team will support the design and evaluation of cyber-physical trust tools that are relevant to real production environments, providing real-world data for other teams to use and keeping the programme grounded in operational reality as it explores how agents can interact securely across digital and physical systems.
Team: Kate Lucas, Ciara Gumsheimer, Ollie Rosen (Matta)