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- W3202017764 abstract "The application of machine learning (ML) algorithms are massively scaling up due to rapid digitization and emergence of new tecnologies like the 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 more. However, all these algorithms need to be trained in order to predict/solve a particular problem. There is high possibility of tampering with the training datasets and producing biased results. Hence, in this article, we propose a blockchain-based solution to secure the datasets generated from IoT devices for e-health applications. The proposed blockchain-based solution uses 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." @default.
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- W3202017764 date "2021-09-01" @default.
- W3202017764 modified "2023-10-01" @default.
- W3202017764 title "Blockchain-Based Attack Detection on Machine Learning Algorithms for IoT-Based e-Health Applications" @default.
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- W3202017764 doi "https://doi.org/10.1109/iotm.1021.2000160" @default.
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