Faithful and Privacy-Preserving Implementation of Average Consensus

2025-03-12

AI Summary

This paper addresses the distributed average consensus problem under rational agents, jointly ensuring incentive compatibility and privacy preservation. We propose a novel framework integrating mechanism design with encrypted control: an incentive-compatible mechanism guarantees agents truthfully follow the protocol; additive homomorphic encryption combined with Shamir’s secret sharing enables fully encrypted iterative updates, provably concealing all agents’ initial values; and under the secure multi-party computation model, simulation-based proofs establish resilience against colluding adversaries. To our knowledge, this is the first work to systematically incorporate mechanism design theory into encrypted control, thereby achieving dual provable guarantees—behavioral trustworthiness against rational adversaries and rigorous data privacy. The framework bridges game-theoretic incentives with cryptographic security, offering a foundational approach for privacy-preserving distributed optimization in adversarial, self-interested settings.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design
• Machine Learning: Privacy

Application Category

• Security and Privacy: Applications of cryptography
• Economics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environments
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

We propose a protocol based on mechanism design theory and encrypted control to solve average consensus problems among rational and strategic agents while preserving their privacy. The proposed protocol provides a mechanism that incentivizes the agents to faithfully implement the intended behavior specified in the protocol. Furthermore, the protocol runs over encrypted data using homomorphic encryption and secret sharing to protect the privacy of agents. We also analyze the security of the proposed protocol using a simulation paradigm in secure multi-party computation. The proposed protocol demonstrates that mechanism design and encrypted control can complement each other to achieve security under rational adversaries.

Problem

• Solves average consensus among strategic agents
• Ensures privacy using homomorphic encryption
• Incentivizes faithful behavior via mechanism design

Innovation

• Uses mechanism design for rational agent behavior
• Employs homomorphic encryption for data privacy
• Integrates secret sharing in secure computation