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

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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Publication Details

Journal
Scientific Reports
Published
2025-08-05
DOI
https://doi.org/10.1038/s41598-025-08784-8
Citations
2
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
2.97

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article

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

Debasis Das, Santanu Chaudhury, Shreyansh Sharma
2 citations
Scientific Reports
Biometric Identification and Security
2.97
article

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

Debasis Das, Santanu Chaudhury, Shreyansh Sharma
article en
2 citations

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.

Scientific ReportsVol. 15(1)
Indian Institute of Technology Jodhpur (IN), Indian Institute of Technology Delhi (IN)
Indian Institute of Technology Jodhpur
Openalex Percentile: Top 8%
Biometric Identification and Security
2.97
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