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Smart Blockchain-Based Access Control for the Internet of Things

arXiv Security Archived Jun 15, 2026 ✓ Full text saved

arXiv:2606.13798v1 Announce Type: new Abstract: Securing access control in large-scale Internet of Things (IoT) deployments requires mechanisms that adapt to risk while preserving low latency for benign traffic. Permissioned blockchains such as Hyperledger Fabric offer auditability through smart contracts, but static endorsement policies impose the same validation depth on all requests, regardless of security posture. We propose a risk-adaptive enforcement layer for Hyperledger Fabric that coupl

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    Computer Science > Cryptography and Security [Submitted on 11 Jun 2026] Smart Blockchain-Based Access Control for the Internet of Things Mahdi Manavi, Yunpeng Zhang, Guoning Chen Securing access control in large-scale Internet of Things (IoT) deployments requires mechanisms that adapt to risk while preserving low latency for benign traffic. Permissioned blockchains such as Hyperledger Fabric offer auditability through smart contracts, but static endorsement policies impose the same validation depth on all requests, regardless of security posture. We propose a risk-adaptive enforcement layer for Hyperledger Fabric that couples an off-chain LSTM-based risk oracle with deterministic on-chain checks. The oracle assigns each request to a tier (Low, Moderate, High) and issues a signed attestation bound to the client identity and target key/version. Endorsing peers verify the attestation in chaincode and enforce tier-conditioned SBE policies without modifying the ordering service or consensus. Experiments on a Fabric testbed show that tier-conditioned endorsement strengthens validation for higher-risk requests while retaining low confirmation latency for benign workloads. Comments: 6 pages, 3 figures. Accepted to the 35th International Conference on Computer Communications and Networks (ICCCN 2026) Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2606.13798 [cs.CR]   (or arXiv:2606.13798v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.13798 Focus to learn more Submission history From: Mahdi Manavi [view email] [v1] Thu, 11 Jun 2026 18:08:29 UTC (417 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
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    ◬ AI & Machine Learning
    Published
    Jun 15, 2026
    Archived
    Jun 15, 2026
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