Preprint: Privacy-preserving IoT Data Sharing Scheme

TL;DR

This paper proposes a privacy-preserving IoT data sharing scheme utilizing broadcast signals and machine learning, achieving up to 97.78% accuracy in experiments.

Contribution

It introduces a novel IoT data sharing scheme based on broadcast signals and ML, with experimental validation demonstrating high accuracy.

Findings

Achieved up to 97.78% accuracy in data sharing

Utilized broadcast signals and ML models for privacy-preserving sharing

Validated scheme through experimental testing

Abstract

Data sharing can be granted using different factors one of which is something in a users or an IoT devices environment which is in this paper broadcast signals. Using broadcast signals to measure Received Signal Strength Indicator values and Machine Learning models this paper implements an IoT data sharing scheme based on something that is in an IoT devices environment. The proposed scheme is experimentally tested using different ML models and shows 97.78 percent as its highest accuracy.