Pragmatic Study of IoT in Healthcare Security with an Explainable AI Perspective

Abstract

The Internet of Things (IoT) is the concept of connecting any device to the Web and other connected gadgets. IoT resembles a ubiquitous network, with the exception that any electrical equipment connected to it has internet connectivity. IoT in the health industry is a great example of this pervasive computing. With the rise of explainable AI, security in IoT using predictive methods is an important concern that needs to be taken care of. If IoT in healthcare is to be successful, serious security issues must be resolved. Medical professionals and society handling IoT devices must ensure that the data collected by IoT devices is appropriately protected and it can be achieved through proper interpretation of results through explainable AI approaches. The main objective of this work is to draw a comparative analysis of two IoT security healthcare strategies in the context of explainable AI aspect. To achieve these objectives, we have discussed two distinct models in this study. The first model takes into account security in intelligent healthcare leveraging block-chain and explainable intelligence. The second model offers a healthcare security method based on easily interpretable deep learning. Also included is a table that compares the two models.

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