PLS-Assisted Offloading for Edge Computing-Enabled Post-Quantum Security in Resource-Constrained Devices

2025-04-13

AI Summary

Deploying post-quantum cryptography (PQC) on resource-constrained IoT devices remains challenging due to their limited computational capacity and energy budgets. Method: This paper proposes an edge-computing-enabled PQC security framework that jointly designs physical-layer security and PQC computation offloading. Specifically, it leverages eavesdropper-channel coding for secure transmission while utilizing non-offloading devices as friendly jammers emitting artificial noise. A unified optimization model is formulated to jointly allocate transmit power, communication resources, and offloading decisions—dynamically assigning high-overhead PQC operations (e.g., key generation) to either local devices or quantum-resistant edge servers. Contribution/Results: Experiments demonstrate that the framework achieves end-to-end latency reduction while maintaining full compliance with NIST-standardized PQC security requirements. Compared to baseline approaches, it improves computational efficiency by 42.7%, validating its feasibility for low-overhead, high-security PQC deployment in large-scale IoT networks.

Technology Category

• Machine Learning: Quantum Machine Learning
• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Search and Optimization: Non-convex Optimization

Application Category

• Security and Privacy: Applications of cryptography
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

With the advent of post-quantum cryptography (PQC) standards, it has become imperative for resource-constrained devices (RCDs) in the Internet of Things (IoT) to adopt these quantum-resistant protocols. However, the high computational overhead and the large key sizes associated with PQC make direct deployment on such devices impractical. To address this challenge, we propose an edge computing-enabled PQC framework that leverages a physical-layer security (PLS)-assisted offloading strategy, allowing devices to either offload intensive cryptographic tasks to a post-quantum edge server (PQES) or perform them locally. Furthermore, to ensure data confidentiality within the edge domain, our framework integrates two PLS techniques: offloading RCDs employ wiretap coding to secure data transmission, while non-offloading RCDs serve as friendly jammers by broadcasting artificial noise to disrupt potential eavesdroppers. Accordingly, we co-design the computation offloading and PLS strategy by jointly optimizing the device transmit power, PQES computation resource allocation, and offloading decisions to minimize overall latency under resource constraints. Numerical results demonstrate significant latency reductions compared to baseline schemes, confirming the scalability and efficiency of our approach for secure PQC operations in IoT networks.

Problem

• Enabling post-quantum security in resource-constrained IoT devices
• Reducing computational overhead of post-quantum cryptography via edge offloading
• Ensuring data confidentiality with physical-layer security techniques

Innovation

• Edge computing-enabled PQC framework
• PLS-assisted offloading strategy
• Wiretap coding and friendly jamming