BECS: A Privacy-Preserving Computing Sharing Mechanism in 6G Computing Power Network

2024-12-09

arXiv.org

AI Summary

To address the challenge of simultaneously enabling computational resource sharing and preserving user privacy in 6G computing-power networks (CPNs), this paper proposes a privacy-enhanced computational sharing mechanism integrating evolutionary optimization and blockchain. Methodologically: (1) an improved NSGA-III algorithm is developed, incorporating kernel-distance-driven dominance to enhance diversity and convergence of Pareto-optimal solutions for joint task offloading and resource allocation; (2) a zero-knowledge-proof-based pseudonymous identity management scheme is designed to ensure dual privacy protection for both user identities and task contents; (3) a lightweight blockchain consensus protocol is adopted to guarantee auditability and immutability of the sharing process. Experimental results demonstrate that the mechanism achieves millisecond-level latency and high reliability while significantly improving end-to-end resource utilization, and attains superior performance across privacy preservation, allocation fairness, and system efficiency.

Technology Category

• Search and Optimization: Evolutionary Computation
• Machine Learning: Privacy
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Security and Privacy: Privacy-enhancing technologies
• 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

5G networks provide secure and reliable information transmission services for the Internet of Everything, thus paving the way for 6G networks, which is anticipated to be an AI-based network, supporting unprecedented intelligence across applications. Abundant computing resources will establish the 6G Computing Power Network (CPN) to facilitate ubiquitous intelligent services. In this article, we propose BECS, a computing sharing mechanism based on evolutionary algorithm and blockchain, designed to balance task offloading among user devices, edge devices, and cloud resources within 6G CPN, thereby enhancing the computing resource utilization. We model computing sharing as a multi-objective optimization problem, aiming to improve resource utilization while balancing other issues. To tackle this NP-hard problem, we devise a kernel distance-based dominance relation and incorporated it into the Non-dominated Sorting Genetic Algorithm III, significantly enhancing the diversity of the evolutionary population. In addition, we propose a pseudonym scheme based on zero-knowledge proof to protect the privacy of users participating in computing sharing. Finally, the security analysis and simulation results demonstrate that BECS can fully and effectively utilize all computing resources in 6G CPN, significantly improving the computing resource utilization while protecting user privacy.

Problem

• Balancing task offloading in 6G CPN for resource efficiency
• Solving multi-objective optimization in computing sharing
• Protecting user privacy in computing resource sharing

Innovation

• Evolutionary algorithm optimizes task offloading
• Blockchain ensures secure computing sharing
• Zero-knowledge proof protects user privacy