Zero-Trust Privacy Enforcement and Threat-Aware Monitoring in Consumer Healthcare Systems

Document Type

Article

Source of Publication

IEEE Transactions on Consumer Electronics

Publication Date

1-1-2026

Abstract

Consumer healthcare applications increasingly rely on AI-driven monitoring, IoMT devices, and continuous data collection, creating critical challenges involving privacy, unauthorized access, excessive surveillance, and secure healthcaredata management. This paper proposes a zero-trust, threataware architecture that integrates context-aware computer vision, blockchain-based decentralized access control, and zero-knowledge proofs for privacy-preserving healthcare monitoring. The framework filters incoming streams to retain only healthcare-relevant events; encrypted records remain off-chain, whereas hashes, access decisions, consent states, and audit logs are recorded on a consortium blockchain. Zero-knowledge proofs support confidential authorization, whereas reputation-aware trust management and blockchain-enabled incentives promote reliable participation and discourage malicious behavior. Clinical events, including falls and abnormal postures, are detected through a CNN-LSTM model, while cybersecurity threats are identified through policy evaluation, transaction validation, and behavioral monitoring. Across 30 independent runs under varied workloads and attack conditions, the proposed architecture achieved a 54.5% reduction in data-access time, a 52.4% reduction in breach-response time, and a 78.1% reduction in privacy and integrity incidents compared with a conventional architecture. Simulated participation increased by 43.7% after incentive deployment across 12 monthly scenarios. These results indicate improved efficiency, privacy preservation, and threat responsiveness for AI-enabled consumer healthcare monitoring.

ISSN

0098-3063

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Disciplines

Computer Sciences

Keywords

Blockchain, Computer Vision, Healthcare Monitoring, Privacy Preservation, Zero-Knowledge Proofs, Zero-Trust Security

Scopus ID

105048724546

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Green: A manuscript of this publication is openly available in a repository

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