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Sovereign AI at the Front Door of Care: A Physically Unidirectional Architecture for Secure Clinical Intelligence

arXiv Security Archived Mar 27, 2026 ✓ Full text saved

arXiv:2603.24898v1 Announce Type: new Abstract: We present a Sovereign AI architecture for clinical triage in which all inference is performed on-device and inbound data is delivered via a physically unidirectional channel, implemented using receive-only broadcast infrastructure or certified hardware data diodes, with no return path to any external network. This design removes the network-mediated attack surface by construction, rather than attempting to secure it through software controls. The

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    Computer Science > Cryptography and Security [Submitted on 26 Mar 2026] Sovereign AI at the Front Door of Care: A Physically Unidirectional Architecture for Secure Clinical Intelligence Vasu Srinivasan, Dhriti Vasu We present a Sovereign AI architecture for clinical triage in which all inference is performed on-device and inbound data is delivered via a physically unidirectional channel, implemented using receive-only broadcast infrastructure or certified hardware data diodes, with no return path to any external network. This design removes the network-mediated attack surface by construction, rather than attempting to secure it through software controls. The system performs conversational symptom intake, integrates device-captured vitals, and produces structured, triage-aligned clinical records at the point of care. We formalize the security properties of receiver-side unidirectionality and show that the architecture is transport-agnostic across broadcast and diode-enforced deployments. We further analyze threat models, enforcement mechanisms, and deployment configurations, demonstrating how physical one-way data flow enables high-assurance operation in both resource-constrained and high-risk environments. This work positions physically unidirectional channels as a foundational primitive for sovereign, on-device clinical intelligence at the front door of care. Comments: 31 pages Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI); Networking and Internet Architecture (cs.NI) MSC classes: 68M10, 68M15, 92C50 ACM classes: C.2.0; K.6.5; J.3 Cite as: arXiv:2603.24898 [cs.CR]   (or arXiv:2603.24898v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2603.24898 Focus to learn more Submission history From: Vasu Srinivasan [view email] [v1] Thu, 26 Mar 2026 00:24:55 UTC (27 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-03 Change to browse by: cs cs.AI cs.NI 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
    Category
    ◬ AI & Machine Learning
    Published
    Mar 27, 2026
    Archived
    Mar 27, 2026
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