Unlinkable and Decentralized Credential Management for Agentic AI

IF 7.3 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2026-01-01 Epub Date: 2026-03-19 DOI:10.1109/TNSE.2026.3695095

Qi Liu;Peng Jiang;Jun Zhu;Shaolong Tang;Wei Wang;Liehuang Zhu

{"title":"Unlinkable and Decentralized Credential Management for Agentic AI","authors":"Qi Liu;Peng Jiang;Jun Zhu;Shaolong Tang;Wei Wang;Liehuang Zhu","doi":"10.1109/TNSE.2026.3695095","DOIUrl":null,"url":null,"abstract":"The evolution toward agentic AI is transforming edge devices from passive sensors into autonomous agents capable of collaborative decision-making. However, the open interaction among these agents exposes the system to malicious intrusions, making robust authentication essential to validate legitimate agents. Traditional authentication mechanisms still suffer from sensitive information leakage due to the potential exposure of agents' real-time locations and session linkability. Furthermore, previous privacy-preserving techniques often employ a centralized manager to prevent information leakage, whose compromise breaks the security of the whole system. In this paper, we propose B-CM, a blockchain-based credential management mechanism for agentic AI. B-CM augments traditional authentication by integrating anonymous credentials with blockchain technology to enable unlinkable and auditable agent authentication in a decentralized manner. To optimize efficiency, we leverage off-chain computation performed by edge servers and fast on-chain verification, accompanied by credential aggregation. We implement B-CM over Hyperledger Fabric to evaluate its performance. Experimental results show that the off-chain computation remains highly efficient, requiring only 8.35 s for distributed key generation and 9.7 ms for credential issuance, while the on-chain computational overhead is nearly negligible.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"13 ","pages":"9379-9393"},"PeriodicalIF":7.3000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11526983/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/3/19 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

The evolution toward agentic AI is transforming edge devices from passive sensors into autonomous agents capable of collaborative decision-making. However, the open interaction among these agents exposes the system to malicious intrusions, making robust authentication essential to validate legitimate agents. Traditional authentication mechanisms still suffer from sensitive information leakage due to the potential exposure of agents' real-time locations and session linkability. Furthermore, previous privacy-preserving techniques often employ a centralized manager to prevent information leakage, whose compromise breaks the security of the whole system. In this paper, we propose B-CM, a blockchain-based credential management mechanism for agentic AI. B-CM augments traditional authentication by integrating anonymous credentials with blockchain technology to enable unlinkable and auditable agent authentication in a decentralized manner. To optimize efficiency, we leverage off-chain computation performed by edge servers and fast on-chain verification, accompanied by credential aggregation. We implement B-CM over Hyperledger Fabric to evaluate its performance. Experimental results show that the off-chain computation remains highly efficient, requiring only 8.35 s for distributed key generation and 9.7 ms for credential issuance, while the on-chain computational overhead is nearly negligible.

查看原文本刊更多论文

代理AI的不可链接和分散凭证管理

人工智能的发展正在将边缘设备从被动传感器转变为能够协同决策的自主代理。然而，这些代理之间的开放交互使系统暴露于恶意入侵，因此对于验证合法代理来说，健壮的身份验证是必不可少的。传统的身份验证机制由于暴露了代理的实时位置和会话链接性，仍然存在敏感信息泄露的问题。此外，以往的隐私保护技术通常采用集中式管理器来防止信息泄露，而信息泄露会破坏整个系统的安全性。在本文中，我们提出了基于区块链的代理AI凭证管理机制B-CM。B-CM通过将匿名凭证与区块链技术集成来增强传统身份验证，以分散的方式支持不可链接和可审计的代理身份验证。为了优化效率，我们利用边缘服务器执行的链下计算和伴随凭据聚合的快速链上验证。我们在Hyperledger Fabric上实现B-CM以评估其性能。实验结果表明，链下计算仍然具有很高的效率，分布式密钥生成和证书颁发仅需8.35 s和9.7 ms，而链上计算开销几乎可以忽略不计。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.