Secure and Verifiable Optional-Dimension Data Aggregation for Efficient WBAN Deployment

Wireless Body Area Networks (WBANs) enable continuous monitoring of vital signs via wearable or implantable biosensors. To reduce cloud-side computation, terminal nodes locally process multidimensional physiological data and forward aggregated results to an intermediate aggregator. However, existing approaches face three key limitations: (1) the lack of terminal verification exposes WBANs to data authenticity risks, including tampering and lazy reporting; (2) privacy-preserving mechanisms such as secret sharing and homomorphic encryption incur high computational overhead, limiting efficiency and scalability; and (3) users are required to share all data dimensions at once, preventing personalized and flexible data sharing. To address these challenges, we propose a secure and verifiable optional-dimension data aggregation scheme SVODA for scalable WBAN deployment. The SVODA scheme integrates differential privacy to enhance protection without extra computational burden, and its effectiveness is validated through noise-error experiments on real-world datasets. It further incorporates a validation step at the aggregator to detect tampered data and identify non-responsive terminals. Moreover, SVODA allows users to selectively share specific data dimensions, enabling aggregation based on user consent rather than indiscriminate aggregation. Finally, we present a comprehensive security analysis and performance evaluation. The results demonstrate that our SVODA scheme is secure, while also achieving superior computational efficiency and storage performance compared to existing methods.