Blockchain based Attack Detection on Machine Learning Algorithms for IoT based E-Health Applications

TL;DR

This paper proposes a blockchain-based system to secure IoT-generated datasets in E-Health applications, aiming to prevent tampering and ensure data integrity for machine learning training.

Contribution

It introduces a novel blockchain solution utilizing private cloud infrastructure to protect IoT datasets in healthcare, enhancing data security and trustworthiness.

Findings

System effectively secures IoT datasets against tampering.

Blockchain implementation ensures data integrity for ML training.

Proposed solution is practical for real-world E-Health applications.

Abstract

The application of machine learning (ML) algorithms are massively scaling-up due to rapid digitization and emergence of new tecnologies like Internet of Things (IoT). In today's digital era, we can find ML algorithms being applied in the areas of healthcare, IoT, engineering, finance and so on. However, all these algorithms need to be trained in order to predict/solve a particular problem. There is high possibility of tampering the training datasets and produce biased results. Hence, in this article, we have proposed blockchain based solution to secure the datasets generated from IoT devices for E-Health applications. The proposed blockchain based solution uses using private cloud to tackle the aforementioned issue. For evaluation, we have developed a system that can be used by dataset owners to secure their data.