Challenges of Privacy-Preserving Machine Learning in IoT [article]

Mengyao Zheng, Dixing Xu, Linshan Jiang, Chaojie Gu, Rui Tan, Peng Cheng
2019 arXiv   pre-print
The Internet of Things (IoT) will be a main data generation infrastructure for achieving better system intelligence. However, the extensive data collection and processing in IoT also engender various privacy concerns. This paper provides a taxonomy of the existing privacy-preserving machine learning approaches developed in the context of cloud computing and discusses the challenges of applying them in the context of IoT. Moreover, we present a privacy-preserving inference approach that runs a
more » ... ghtweight neural network at IoT objects to obfuscate the data before transmission and a deep neural network in the cloud to classify the obfuscated data. Evaluation based on the MNIST dataset shows satisfactory performance.
arXiv:1909.09804v1 fatcat:4jek6hmekvbkjp5id2r52m2cpu