Secure Autonomous Agent Payments: Verifying Authenticity and Intent in a Trustless Environment
This work addresses the problem of secure and auditable financial transactions for AI agents in decentralized systems, representing a foundational step towards verifiable trust in AI-driven economies.
The paper tackles the challenge of verifying authenticity and intent in autonomous AI agent payments in trustless environments, proposing a blockchain-based framework that uses cryptographic methods to authenticate agents and verify transaction intent, demonstrating strong resistance to impersonation and unauthorized transactions.
Artificial intelligence (AI) agents are increasingly capable of initiating financial transactions on behalf of users or other agents. This evolution introduces a fundamental challenge: verifying both the authenticity of an autonomous agent and the true intent behind its transactions in a decentralized, trustless environment. Traditional payment systems assume human authorization, but autonomous, agent-led payments remove that safeguard. This paper presents a blockchain-based framework that cryptographically authenticates and verifies the intent of every AI-initiated transaction. The proposed system leverages decentralized identity (DID) standards and verifiable credentials to establish agent identities, on-chain intent proofs to record user authorization, and zero-knowledge proofs (ZKPs) to preserve privacy while ensuring policy compliance. Additionally, secure execution environments (TEE-based attestations) guarantee the integrity of agent reasoning and execution. The hybrid on-chain/off-chain architecture provides an immutable audit trail linking user intent to payment outcome. Through qualitative analysis, the framework demonstrates strong resistance to impersonation, unauthorized transactions, and misalignment of intent. This work lays the foundation for secure, auditable, and intent-aware autonomous economic agents, enabling a future of verifiable trust and accountability in AI-driven financial ecosystems.