Securing the Future of IoMT in the Post-Quantum Era: An Edge-Native Federated Learning Approach
arXiv:2606.14515v1 Announce Type: cross Abstract: Internet of Medical Things (IoMT) devices operate under strict resource constraints while handling highly sensitive health data, making security and privacy critical concerns. Federated learning (FL) further complicates this landscape, as model updates exchanged during training may unintentionally expose private medical information. Emerging quantum computing capabilities threaten the long-term viability of conventional lightweight cryptographic mechanisms, motivating the integration of Post-Quantum Cryptography (PQC) into IoMT systems. This ar
The proliferation of IoMT devices, coupled with the increasing threat of quantum computing, necessitates immediate action to secure sensitive medical data and prevent future vulnerabilities.
This development highlights the critical need for integrating advanced cryptographic solutions into healthcare infrastructure to protect patient privacy and device integrity against emerging cyber threats.
The adoption of Post-Quantum Cryptography (PQC) and edge-native federated learning will become a standard requirement for IoMT security, shifting how medical data is protected and processed.
- · Cybersecurity firms specializing in PQC
- · IoMT device manufacturers adopting PQC
- · Healthcare providers with secure data infrastructure
- · Patients benefiting from enhanced data privacy
- · IoMT manufacturers slow to adopt PQC
- · Healthcare systems with legacy security protocols
- · Attackers leveraging quantum computing capabilities
Increased research and development in quantum-resistant security solutions for edge computing.
New regulatory frameworks and compliance standards for IoMT security, mandating PQC integration.
A competitive landscape where IoMT security becomes a primary differentiator for device and service providers.
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