Adaptive Lightweight Security for Performance Efficiency in Critical Healthcare Monitoring

TL;DR

This paper addresses the security-performance tension in IoMT by evaluating lightweight cryptography within MQTT-based remote patient monitoring. It proposes an experimental framework comparing No Cipher, AES-128-GCM, ASCON-128, and TLSv1.2 across Raspberry Pi and laptop edge scenarios over a 5G link, highlighting ASCON-128 as highly efficient for small messages while noting size-dependent limits. The main contributions include a practical RPM use case, a structured experimental setup, and a performance analysis demonstrating that adaptive, lightweight security can improve timely, secure healthcare communications. The findings support deploying ASCON-128 for low-latency RPM data and inform design choices for secure, resource-constrained healthcare IoT deployments in evolving networks.

Abstract

The healthcare infrastructure requires robust security procedures, technologies, and policies due to its critical nature. Since the Internet of Things (IoT) with its diverse technologies has become an integral component of future healthcare systems, its security requires a thorough analysis due to its inherent security limitations that arise from resource constraints. Existing communication technologies used for IoT connectivity, such as 5G, provide communications security with the underlying communication infrastructure to a certain level. However, the evolving healthcare paradigm requires adaptive security procedures and technologies that can adapt to the varying resource constraints of IoT devices. This need for adaptive security is particularly pronounced when considering components outside the security sandbox of 5G, such as IoT nodes and M2M connections, which introduce additional security challenges. This article brings forth the unique healthcare monitoring requirements and studies the existing encryption-based security approaches to provide the necessary security. Furthermore, this research introduces a novel approach to optimizing security and performance in IoT in healthcare, particularly in critical use cases such as remote patient monitoring. Finally, the results from the practical implementation demonstrate a marked improvement in the system performance.

Figures (7)

• Figure 1: MQTT architecture and protocol.
• Figure 2: MQTT (QoS 1) Communication Sequence Diagram.
• Figure 3: Remote Patient Monitoring (RPM) - Use case Diagram.
• Figure 4: Network Topology Diagram.
• Figure 5: Performance Efficiency of ASCON.