Cryptographic measures secure communication between AI agents in multi-agent systems
Cryptographically Secure Agent-to-Agent Communication in Multi-Agent Systems
Cryptography and SecurityMultiagent Systems
Summary
In systems where multiple AI agents work together or compete, it's important to keep their messages safe from hackers who might try to impersonate agents or steal information. The paper explains challenges in making this communication secure and offers a new design combining strong identity checks, encrypted message transport, and monitoring to catch unusual behavior. This design uses advanced cryptography, like decentralized IDs, secure messaging formats, and special proofs that keep data private while verifying rules. Together, these tools help protect agent communications and can be useful even for future types of AI networks.
What this means in practice
- •For cloud security teams: Protect inter-service AI communications within cloud platforms by integrating decentralized identity and hybrid post-quantum secure transport described in the paper.
- •For telecommunications engineers: Design semantic communication protocols for 6G networks that incorporate cryptographic identity and integrity methods like those surveyed for multi-agent systems.
A survey. It maps existing work.
Authors
Karol Budzyn, Adrian Brodzik, Mateusz Szczepkowski
Abstract
Multi-agent systems (MAS) comprise AI agents that collaborate or compete to perform complex, distributed tasks. Their dynamic interactions create opportunities for threat actors to target and impersonate other agents, intercept messages, inject malicious prompts, and exfiltrate sensitive data while simultaneously complicating the detection of anomalous behavior through conventional monitoring. This paper surveys threats and cryptographic challenges in agent-to-agent communication and presents a zero-trust architecture integrating identity, transport security, message integrity, and monitoring. The architecture establishes agent identities via decentralized identifiers and task-scoped verifiable credentials backed by a permissioned ledger, enforcing least-privilege authorization. For transport security, it provides mutually authenticated, crypto-agile TLS with hybrid post-quantum key establishment, and evaluates KEMTLS with pre-distributed public keys to reduce handshake overhead. Signed CBOR envelopes preserve payload integrity across multi-hop exchanges, while zero-knowledge proofs verify declared task constraints without exposing underlying inputs. Context-aware monitoring of inter-agent messages, tool activity, and execution telemetry informs the setting of risk-based trust thresholds and supports the detection of behavioral anomalies. Together, these mechanisms provide an integrated framework for securing and auditing agent communication, with implications for other agentic protocols and prospective 6G semantic communication.