A decentralized privacy-preserving XR system for 3D medical data visualization using hybrid biometric cryptosystem

Abstract In the era of digital healthcare, accurate and secure 3D visualization of medical data is critical for collaborative surgical planning. Traditional centralized systems suffer from security vulnerabilities and lack of depth cues necessary for accurate visualization of complex anatomy. We pre...

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Main Authors: Shreyansh Sharma, Debasis Das, Santanu Chaudhury
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-08784-8
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author Shreyansh Sharma
Debasis Das
Santanu Chaudhury
author_facet Shreyansh Sharma
Debasis Das
Santanu Chaudhury
author_sort Shreyansh Sharma
collection DOAJ
description Abstract In the era of digital healthcare, accurate and secure 3D visualization of medical data is critical for collaborative surgical planning. Traditional centralized systems suffer from security vulnerabilities and lack of depth cues necessary for accurate visualization of complex anatomy. We present a decentralized Extended Reality (XR)-based framework integrating a Hybrid Biometric Cryptosystem (HBC), hierarchical redactable blockchain, and InterPlanetary File System (IPFS)-based storage to address these limitations. The HBC combines leveled Homomorphic Encryption (HE) and Fuzzy Vault (FV) schemes for privacy-preserving multimodal biometric authentication. A hierarchical blockchain ensures tamper-resistance, consensus-based redactions, and secure access control. Photorealistic, spatially registered 3D models of brain MRI data are rendered in Augmented Reality (AR) and Mixed Reality (MR), enabling intuitive surgical planning. Edge caching accelerates data retrieval, enabling real-time interaction. Real-world deployment on Android and HoloLens 2 platforms demonstrates the clinical utility and robustness of the proposed framework. Security analysis confirms resistance to security threats such as replay, spoofing, etc, and unauthorized redactions. We achieve Equal Error Rates (EER) of 0.53% in AR and 0.68% in MR environments, with average authentication latency under 530 ms. A structured user study involving 40 clinicians confirms the system’s clinical utility, usability, and compliance with GDPR (General Data Protection Regulation) and HIPAA (Health Insurance Portability and Accountability Act) regulations. Therefore, the proposed framework offers a scalable, secure, and immersive platform for collaborative medical data visualization in digital healthcare.
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spelling doaj-art-18a3404ad6b64467aff932d551782fec2025-08-20T04:03:01ZengNature PortfolioScientific Reports2045-23222025-08-0115112210.1038/s41598-025-08784-8A decentralized privacy-preserving XR system for 3D medical data visualization using hybrid biometric cryptosystemShreyansh Sharma0Debasis Das1Santanu Chaudhury2Department of Computer Science and Engineering, Indian Institute of Technology JodhpurDepartment of Computer Science and Engineering, Indian Institute of Technology JodhpurDepartment of Electrical Engineering, Indian Institute of Technology DelhiAbstract In the era of digital healthcare, accurate and secure 3D visualization of medical data is critical for collaborative surgical planning. Traditional centralized systems suffer from security vulnerabilities and lack of depth cues necessary for accurate visualization of complex anatomy. We present a decentralized Extended Reality (XR)-based framework integrating a Hybrid Biometric Cryptosystem (HBC), hierarchical redactable blockchain, and InterPlanetary File System (IPFS)-based storage to address these limitations. The HBC combines leveled Homomorphic Encryption (HE) and Fuzzy Vault (FV) schemes for privacy-preserving multimodal biometric authentication. A hierarchical blockchain ensures tamper-resistance, consensus-based redactions, and secure access control. Photorealistic, spatially registered 3D models of brain MRI data are rendered in Augmented Reality (AR) and Mixed Reality (MR), enabling intuitive surgical planning. Edge caching accelerates data retrieval, enabling real-time interaction. Real-world deployment on Android and HoloLens 2 platforms demonstrates the clinical utility and robustness of the proposed framework. Security analysis confirms resistance to security threats such as replay, spoofing, etc, and unauthorized redactions. We achieve Equal Error Rates (EER) of 0.53% in AR and 0.68% in MR environments, with average authentication latency under 530 ms. A structured user study involving 40 clinicians confirms the system’s clinical utility, usability, and compliance with GDPR (General Data Protection Regulation) and HIPAA (Health Insurance Portability and Accountability Act) regulations. Therefore, the proposed framework offers a scalable, secure, and immersive platform for collaborative medical data visualization in digital healthcare.https://doi.org/10.1038/s41598-025-08784-83D medical data visualizationXRHBCRedactable blockchainPrivacy-preserving healthcare
spellingShingle Shreyansh Sharma
Debasis Das
Santanu Chaudhury
A decentralized privacy-preserving XR system for 3D medical data visualization using hybrid biometric cryptosystem
Scientific Reports
3D medical data visualization
XR
HBC
Redactable blockchain
Privacy-preserving healthcare
title A decentralized privacy-preserving XR system for 3D medical data visualization using hybrid biometric cryptosystem
title_full A decentralized privacy-preserving XR system for 3D medical data visualization using hybrid biometric cryptosystem
title_fullStr A decentralized privacy-preserving XR system for 3D medical data visualization using hybrid biometric cryptosystem
title_full_unstemmed A decentralized privacy-preserving XR system for 3D medical data visualization using hybrid biometric cryptosystem
title_short A decentralized privacy-preserving XR system for 3D medical data visualization using hybrid biometric cryptosystem
title_sort decentralized privacy preserving xr system for 3d medical data visualization using hybrid biometric cryptosystem
topic 3D medical data visualization
XR
HBC
Redactable blockchain
Privacy-preserving healthcare
url https://doi.org/10.1038/s41598-025-08784-8
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