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D-MUTRA: DLT-based MUTual Remote Attestation for Multi-Agent Systems

Aug 2026 · 0 citations · 34 references
Computer Science

TL;DR

D-MUTRA is a blockchain-based framework that introduces a mutual RA protocol in which agents measure their runtime integrity while verifying that of their peers, acting as both prover and verifier, and scales to large deployments with negligible overhead on protected applications.

Abstract

Multi-agent systems (MAS) comprise autonomous software agents that collaborate to perform complex tasks in critical cyber-physical domains, including multi-robot coordination and the Industrial Internet of Things (IIoT). In such distributed environments, a compromised agent may execute modified software while appearing trustworthy, causing other agents to act on false information and corrupting the mission. Agents must therefore establish and maintain mutual trust throughout operation. Remote attestation (RA) is a well-established technique for this purpose, enabling a remote verifier to assess the integrity of a potentially compromised prover device. However, conventional RA approaches face significant limitations in MAS: integrity guarantees are restricted to boot or application-load time, designs rely on centralized trusted verifiers or security hardware, and attestation records lack transparency and auditability. To address these limitations, this paper presents D-MUTRA, a blockchain-based framework that introduces a mutual RA protocol in which agents measure their runtime integrity while verifying that of their peers, acting as both prover and verifier. The framework operates entirely in software and relies on two components: a Security-as-a-Service that instruments agents with lightweight measurement and verification capabilities, and a smart contract that coordinates the attestation protocol in a decentralized and transparent manner. We implement a proof-of-concept on a private Ethereum blockchain using Hyperledger Besu and evaluate it in a swarm robotics scenario built with Robot Operating System (ROS) and the Gazebo simulator. Results show that D-MUTRA enables agents to continuously attest one another, detects malicious software modifications, and scales to large deployments with negligible overhead on protected applications.

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