A Survey on Privacy-Preserving Signal Processing and Transmission

Abstract

With more and more technologies such as Internet of Things (IoT) and Artificial Intelligence (AI), all kinds of signal data from biometric records to location trajectories have become an indispensable part of modern intelligent systems. Although these data are very useful, because they are particularly sensitive and bring great privacy risks, protecting them has become a key problem in technological development. By analyzing the whole life cycle of signal processing and transmission, this paper systematically combs the Privacy-Preserving Computing (PPC) technology. We have worked out a clear technical route by studying the functions of key PPC technologies (including Homomorphic Encryption, Secure Multi-Party Computation and Federated Learning) in various stages of data collection, transmission, storage and analysis. Through in- depth analysis of the latest solutions in key applications such as Intelligent Transportation Systems (ITS) and Internet of Medical Things (IoMT), this study has made clear the applicable scenarios, advantages and limitations of each technology. Finally, this work aims to help researchers and engineers develop safer and more credible signal processing technology by pointing out the current challenges and future research directions.