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<p>In the current era, healthcare is precious for all, so recent technology helps monitor the patient’s health via sensors and nodes, collect the same data, and analyze the patient’s condition. This is a technology known as a wireless body area network (WBAN). Nano-sensor devices are attached to the human body as part of WBAN to collect and monitor patient data, but have limited processing power and battery life. So, it cannot perform heavy computations within the node. Edge computing addresses this issue by processing data and reducing response times (in a near-edge node), which also helps mitigate delays and offloads work from WBAN nodes, but creates a privacy risk. Sensitive patient health information can be exposed through cyberattacks, unauthorized access, or profiling from edge nodes. This research proposes that PrivEdge-WBAN (Privacy-Preserving Edge Computing for WBANs) is integrated with edge computing, creates a framework for authentication and secure data processing, and supports new privacy-preserving and energy-efficient techniques. The proposed model combines lightweight Homomorphic Encryption (HE) and Differential Privacy (DP) to enable privacy-preserving computations and security at the edge node while maintaining energy efficiency. Moreover, the proposed framework combines an adaptive security engine that dynamically regulates cryptographic processes and authentication complexity derived from real-time energy levels and device workload. PrivEdge-WBAN aims to provide a comprehensive solution for security, privacy, and battery conservation in the real-world applications of WBAN. The outcome of this research can significantly influence the design of sustainable and secure surveillance systems for the healthcare sector, particularly for chronic illnesses, aging care, and other emergencies.</p>

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HEDP-WBAN: Homomorphic Encryption and Differential Privacy for Secure Edge-Based WBANs

  • 期刊论文

  • 发表日期：

    2026年3月30日

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  • Boopathi S,
  • Jothikumar R,
  • Sudhakar T,
  • Vinayakumar Ravi,
  • Alanoud Al Mazroa

摘要

In the current era, healthcare is precious for all, so recent technology helps monitor the patient’s health via sensors and nodes, collect the same data, and analyze the patient’s condition. This is a technology known as a wireless body area network (WBAN). Nano-sensor devices are attached to the human body as part of WBAN to collect and monitor patient data, but have limited processing power and battery life. So, it cannot perform heavy computations within the node. Edge computing addresses this issue by processing data and reducing response times (in a near-edge node), which also helps mitigate delays and offloads work from WBAN nodes, but creates a privacy risk. Sensitive patient health information can be exposed through cyberattacks, unauthorized access, or profiling from edge nodes. This research proposes that PrivEdge-WBAN (Privacy-Preserving Edge Computing for WBANs) is integrated with edge computing, creates a framework for authentication and secure data processing, and supports new privacy-preserving and energy-efficient techniques. The proposed model combines lightweight Homomorphic Encryption (HE) and Differential Privacy (DP) to enable privacy-preserving computations and security at the edge node while maintaining energy efficiency. Moreover, the proposed framework combines an adaptive security engine that dynamically regulates cryptographic processes and authentication complexity derived from real-time energy levels and device workload. PrivEdge-WBAN aims to provide a comprehensive solution for security, privacy, and battery conservation in the real-world applications of WBAN. The outcome of this research can significantly influence the design of sustainable and secure surveillance systems for the healthcare sector, particularly for chronic illnesses, aging care, and other emergencies.