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arXiv 2602.08014cs.CRcs.AI

ICBAC: 一种基于智能合约的访问控制框架，通过整合区块链与联邦学习用于供应链管理

ICBAC: an Intelligent Contract-Based Access Control framework for supply chain management by integrating blockchain and federated learning

Department of Computer Engineering Ferdowsi University of Mashhad（计算机工程系法尔多斯大学）

Sadegh Sohani, Salar Ghazi, Farnaz Kamranfar, Sahar Pilehvar Moakhar, Mohammad Allahbakhsh, Haleh Amintoosi, Kaiwen Zhang

备注：
19 pages, 6 Figures, 3 Tables
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AI总结：

ICBAC通过整合区块链与联邦学习，提供一种动态、隐私保护的访问控制框架，用于解决供应链中的访问控制问题。

摘要：

本文针对现代供应链中访问控制的关键挑战，即供应链跨多个独立且竞争的组织运作。现有访问控制是静态且集中的，无法适应内部威胁或不断变化的环境。区块链提高了去中心化程度，但缺乏行为智能，而集中式机器学习进行异常检测需要聚合敏感数据，从而违反隐私。所提出的解决方案是ICBAC，一种基于智能合约的访问控制框架。它整合了许可区块链（Hyperledger Fabric）与联邦学习（FL）。基于Fabric，ICBAC采用多通道架构和三个智能合约用于资产管理和基础访问控制以及动态撤销。为了对抗内部滥用，每个通道部署一个AI代理，监控活动并动态限制异常访问。联邦学习使这些代理能够协同改进检测模型，而无需共享原始数据。对于异构、竞争性环境，ICBAC引入了基于 hedonic 联盟形成的博弈论客户端选择机制。这使供应链能够通过基于偏好的选择形成稳定、策略无害的 FL 联盟，而无需披露敏感标准。在 Fabric 测试床和真实世界数据集上的大量实验表明，ICBAC 实现了与静态框架相当的区块链性能，并在 IID 和非 IID 数据下提供有效的异常检测，且不共享原始数据。因此，ICBAC 为去中心化供应链中的动态、隐私保护的访问控制提供了实用且可扩展的解决方案。

英文摘要：

This paper addresses the critical challenge of access control in modern supply chains, which operate across multiple independent and competing organizations. Existing access control is static and centralized, unable to adapt to insider threats or evolving contexts. Blockchain improves decentralization but lacks behavioral intelligence, while centralized machine learning for anomaly detection requires aggregating sensitive data, violating privacy. The proposed solution is ICBAC, an intelligent contract-based access control framework. It integrates permissioned blockchain (Hyperledger Fabric) with federated learning (FL). Built on Fabric, ICBAC uses a multi-channel architecture and three smart contracts for asset management, baseline access control, and dynamic revocation. To counter insider misuse, each channel deploys an AI agent that monitors activity and dynamically restricts access for anomalies. Federated learning allows these agents to collaboratively improve detection models without sharing raw data. For heterogeneous, competitive environments, ICBAC introduces a game-theoretic client selection mechanism using hedonic coalition formation. This enables supply chains to form stable, strategy-proof FL coalitions via preference-based selection without disclosing sensitive criteria. Extensive experiments on a Fabric testbed with a real-world dataset show ICBAC achieves blockchain performance comparable to static frameworks and provides effective anomaly detection under IID and non-IID data with zero raw-data sharing. ICBAC thus offers a practical, scalable solution for dynamic, privacy-preserving access control in decentralized supply chains.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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