QuanBioTrust: a quantum-enhanced bio-inspired trust framework for next-generation WBANs

Area of Science:

• Biomedical engineering
• Network security
• Quantum computing

Background:

• Wireless Body Area Networks (WBANs) face challenges in energy efficiency, security, and real-time reliability for continuous biomedical monitoring.
• Conventional protocols struggle with energy constraints, cyberattack vulnerability, and high latency.

Purpose of the Study:

• Propose QuanBioTrust, a novel framework integrating quantum optimization, bio-inspired intelligence, and dynamic zero-trust security.
• Create a scalable, secure, and self-sustaining WBAN architecture for enhanced healthcare monitoring.

Main Methods:

• Quantum Particle Swarm Optimization (QPSO) for cluster head selection, considering energy, proximity, trust, and bio-energy harvesting.
• Bio-inspired algorithms: flocking for mobility-adaptive clustering, firefly synchronization for multi-hop routing, and slime mold for data fusion.
• Dynamic zero-trust security model for robust protection against cyber threats.

Main Results:

• Reduced computational complexity by 28-45% (approx. 500 operations per round).
• Achieved 50-70% ECG packet compression (200-bit to 80-bit), significantly lowering transmission energy.
• Maintained high Packet Delivery Ratio (PDR) of 97% (90% under attack) and low end-to-end latency (48 ms, 185 ms under attack).

Conclusions:

• QuanBioTrust establishes a new paradigm for next-generation WBANs.
• Offers a robust, energy-efficient, and resilient solution for secure, long-term, real-time healthcare monitoring.
• Successfully addresses critical limitations of conventional WBAN protocols.