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IEEE Internet of Things Journal

Edge-Computing-Based Scheme for Post-Quantum IoT Security for e-Health

Noman Nasir Minhas, Khwaja Mansoor

Published Jun 25, 2024• 17 citations
Publisher

Abstract

Internet of Things (IoT) devices are going to be the primary data source in smart cities, often generating and communicating critical, sensitive, and private data that face threats of confidentiality breaches due to the rise of quantum computers. Even though NIST has approved post-quantum cryptography (PQC) schemes that promise to protect from quantum computer threats, these schemes can not be implemented efficiently on IoT devices, which often have computational and memory constraints. Hence, due to the substantial key size requirements and computationally intensive nature of PQC schemes, their direct deployment on IoT devices within smart city architecture is impeded by inherent computational and storage limitations. Consequently, it is imperative to devise PQC-based, resource-efficient authentication protocols tailored to IoT devices operating within smart cities. In this paper, we propose an offloading scheme that uses PQ Edge Server (PQES) for the network that performs PQC-related computation and memory operations for IoT devices in the network. The suggested technique transfers all storage and processing responsibilities from IoT devices in a network to ensure their normal operation and performance without any compromise. PQES generates a distinct PQ key pair for every network device and oversees a separate stream for each device. Therefore, IoT devices in the network may function without cryptographic processes, improving their efficiency by removing the need for conventional cryptography. Our results show that the proposed scheme reduces RAM usage to 1.05 KB and CPU usage to 1.75%, with maximum CPU context switches of 92.8. The proposed scheme uses TCP, a transport layer protocol, which is applicable to lightweight end devices without application-level protocols like HTTP or MQTT. When benchmarked on a Raspberry Pi, the PQES can handle 1000 concurrent connections and use a maximum of 73.5% of RAM. In comparison, previous research used at least 5.1 MB of RAM for one concurrent connection and may use up to 552.6 MB of RAM for 1000 concurrent connections. The maximum CPU usage for our method was 1.75%, whereas the previous proposal had a utilization of 67.1%. The greatest CPU context switches for our system were 92.8, far lower than the 3449 observed for the usual approach. Hence, our proposed scheme reduces the computational, memory, and network load for IoT devices by manifolds and increases device performance while providing PQC security.

DOI
10.1109/jiot.2024.3418959

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Internet of Things (IoT) devices are going to be the primary data source in smart cities, often generating and communicating critical, sensitive, and private data that face threats of confidentiality breaches due to the rise of quantum computers. Even though NIST has approved post-quantum cryptography (PQC) schemes that promise to protect from quantum computer threats, these schemes can not be implemented efficiently on IoT devices, which often have computational and memory constraints. Hence, due to the substantial key size requirements and computationally intensive nature of PQC schemes, their direct deployment on IoT devices within smart city architecture is impeded by inherent computational and storage limitations. Consequently, it is imperative to devise PQC-based, resource-efficient authentication protocols tailored to IoT devices operating within smart cities. In this paper, we propose an offloading scheme that uses PQ Edge Server (PQES) for the network that performs PQC-related computation and memory operations for IoT devices in the network. The suggested technique transfers all storage and processing responsibilities from IoT devices in a network to ensure their normal operation and performance without any compromise. PQES generates a distinct PQ key pair for every network device and oversees a separate stream for each device. Therefore, IoT devices in the network may function without cryptographic processes, improving their efficiency by removing the need for conventional cryptography. Our results show that the proposed scheme reduces RAM usage to 1.05 KB and CPU usage to 1.75%, with maximum CPU context switches of 92.8. The proposed scheme uses TCP, a transport layer protocol, which is applicable to lightweight end devices without application-level protocols like HTTP or MQTT. When benchmarked on a Raspberry Pi, the PQES can handle 1000 concurrent connections and use a maximum of 73.5% of RAM. In comparison, previous research used at least 5.1 MB of RAM for one concurrent connection and may use up to 552.6 MB of RAM for 1000 concurrent connections. The maximum CPU usage for our method was 1.75%, whereas the previous proposal had a utilization of 67.1%. The greatest CPU context switches for our system were 92.8, far lower than the 3449 observed for the usual approach. Hence, our proposed scheme reduces the computational, memory, and network load for IoT devices by manifolds and increases device performance while providing PQC security.
With the advent of post-quantum cryptography (PQC) standards, it has become imperative for resourceconstrained 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.
The impending realization of quantum computing is a threat to the underlying security model of traditional cryptographic infrastructure, especially on the one based on Internet of Things (IoT) and edge computing setups. The post quantum cryptography (PQC) provides quantum resistant protocols that ensure quantum security against a combination of both classical and future quantum attackers, but adopting this technology in edge IoT ecosystems faces serious challenges in terms of resource limitations of low power devices. The paper suggests a performance-security model of PQC in edge IoT explaining the tradeoff between cryptographic robustness and operation efficiency. This model is a synthesis of empirical research in the recent field which looking at the performance of PQC algorithms on limited hardware, the integration issue with lightweight communication protocols, and strategic options such as algorithm optimization, hardware acceleration, hybrid cryptographic schemes, and offloading methods. The objectives of these strategies are to achieve the acceptable latency and energy consumption with the guarantee of quantum resilient security. The framework proposed helps decision making among researchers and practitioners who aim at implementing PQC on distributed resource limited IoT networks. Lastly, the paper also determines the research gaps and future directions to the achievement of scalable, efficient, and robust PQC enabled edge IoT ecosystems.
The impending realization of quantum computing is a threat to the underlying security model of traditional cryptographic infrastructure, especially on the one based on Internet of Things (IoT) and edge computing setups. The post quantum cryptography (PQC) provides quantum resistant protocols that ensure quantum security against a combination of both classical and future quantum attackers, but adopting this technology in edge IoT ecosystems faces serious challenges in terms of resource limitations of low power devices. The paper suggests a performance-security model of PQC in edge IoT explaining the tradeoff between cryptographic robustness and operation efficiency. This model is a synthesis of empirical research in the recent field which looking at the performance of PQC algorithms on limited hardware, the integration issue with lightweight communication protocols, and strategic options such as algorithm optimization, hardware acceleration, hybrid cryptographic schemes, and offloading methods. The objectives of these strategies are to achieve the acceptable latency and energy consumption with the guarantee of quantum resilient security. The framework proposed helps decision making among researchers and practitioners who aim at implementing PQC on distributed resource limited IoT networks. Lastly, the paper also determines the research gaps and future directions to the achievement of scalable, efficient, and robust PQC enabled edge IoT ecosystems.
The rapid expansion of the Internet of Things (IoT) has connected billions of devices, creating a global network that manages everything from smart homes to critical industrial infrastructure. However, this connectivity faces an existential threat: the rise of Quantum Computing. Standard encryption methods like RSA and ECC, which currently protect these devices, will be easily broken by future quantum computers using Shor's Algorithm. While the National Institute of Standards and Technology (NIST) has standardized new "Post-Quantum" algorithms (like Kyber and Dilithium), simply plugging them into small IoT devices is not easy. These new algorithms are often heavy, and IoT devices have very limited battery and processing power. This paper bridges this gap by proposing "PQ-IoT", a complete, end-to-end security framework designed specifically for the real-world constraints of IoT. Unlike previous studies that look at algorithms in isolation, we designed a unified system with three layers: (1) A robust Hybrid Cryptosystem (X25519 + Kyber-768) for secure servers, (2) A lightweight encryption module (Kyber-512) for battery-powered sensors, and (3) A fast authentication mechanism (ML-DSA-44) for gateways. We built a virtual laboratory using ARM64 emulation to test this framework. Our results show that the entire system is incredibly efficient, with encryption taking only 0.20 ms and verification taking 0.50 ms. This proves that we can secure the future of IoT without sacrificing performance.
Internet of Things (IoT) is growing, leading to enhanced data exchange in several areas. Achieving maximum security in the IoT environment is still under the open research. Protecting the confidential data from the external environment in complication for the applications of IoT network. For that purpose, in this article presents a Quantum Computing-Based Cryptography Model with Task Offloading and Data Management (QCCTOD) designed to enhance security and efficiency in IoT networks. It consists of a three-tier architecture, which includes a perceptual tier for data gathering, a network tier that incorporates lightweight cryptography to ensure secure data transmission via sophisticated signature methods to avert data modification, and an application tier for smart decision-making. An intelligent caching system that stores commonly used services from E-APs, improving service provision. The communication model uses an enhanced method for SINR to guarantee swift and effective data transfer while maintaining Quality of Service (QoS). The task offloading process shifts demanding computing tasks from devices with constrained resources to edge servers. This method evaluates energy and latency expenses to find equilibrium between computation and transmission lags, reducing power usage and improving efficiency for IoT applications. A lightweight bio-latticed cryptographic addresses IoT security for the post-quantum era, utilizing methods like the Shortest Vector Problem (SVP) and Galois field computations. The implementation of the proposed QCCTOD is carried out in python and the parameters which are measured to validate the network performance are include signature size analysis, throughput, packet success rate, energy consumption, and network usage. From the final comparison it is proven that the proposed QCCTOD attain better overall performance in terms of network security and data management.
The proliferation of Internet of Things (IoT) devices that use the Message Queuing Telemetry Transport (MQTT) protocol poses significant security challenges in the emerging quantum computing era. Current Transport Layer Security (TLS) implementations rely on classical cryptographic algorithms vulnerable to Shor's algorithm. This paper proposes PQ-MQTT, a hybrid post-quantum secure communication protocol that integrates ML-KEM-768 with X25519 for key encapsulation and a lightweight session-key derivation mechanism optimized for resource-constrained IoT publishers. We present a formal security analysis under the Quantum Random Oracle Model (QROM), demonstrating resilience against store-now-decryptlater attacks. Experimental evaluation on the Raspberry Pi 4, ESP32, and Arduino Nano 33 platforms shows that PQ-MQTT achieves handshake latencies of127.3 ms,412.7 ms127.3 ~\text{ms}, 412.7 ~\text{ms}127.3 ms,412.7 ms, and1,847.2 ms1,847.2 ~\text{ms}1,847.2 ms, respectively, with 18.2 KB of additional memory overhead. A comparative analysis of pure post-quantum and classical TLS implementations shows energy reductions of23.5%−40.5%23.5 \%-40.5 \%23.5%−40.5%relative to pure PQC, achieved through our hybrid optimization approach, while maintaining 94.2 % throughput efficiency.