Federated IoT Networks Protection with AI
Abstract
The combination of artificial intelligence with the Internet of things has greatly enhanced the smart system by providing data driven insights for the real time decision making. But the amount of data generated by IOT devices in the Federated Network Communication specially when the data is very sensitive to the user privacy concerns have become more serious. To address this issue, we come up with the idea of privacy preserving methods which includes homomorphic encryption and differential privacy. The purpose of this paper is to investigate how homomorphic encryption and differential privacy can be use within Federated IOT system to improve data security while maintaining artificial intelligence model performance.
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References
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