Adaptive Lightweight Security for Performance Efficiency in Critical Healthcare Monitoring

TL;DR

This paper proposes an adaptive lightweight security approach tailored for IoT healthcare monitoring systems, balancing security needs with resource constraints to enhance performance in critical healthcare scenarios.

Contribution

It introduces a novel adaptive security method specifically designed for resource-limited IoT healthcare devices, improving security and efficiency over existing approaches.

Findings

Enhanced system performance in practical implementation

Effective security adaptation to resource constraints

Improved security in critical healthcare IoT applications

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.