Encrypted Signal Processing for Privacy Protection

TitleEncrypted Signal Processing for Privacy Protection
Publication TypeJournal Article
Year of Publication2013
AuthorsLagendijk, RL, Erkin, Z, Barni, M
JournalIEEE Signal Processing Magazine
Date PublishedJanuary 2013
KeywordsApplied cryptography, collaborative filtering, Face recognition, Homomorphic Encryption, K-means clustering, Privacy protection, Privacy-sensitive design, Secure multiparty computing, Signal processing

In recent years, signal processing applications that deal with user-related data have aroused privacy concerns. For instance, face recognition and personalized recommendations rely on privacy-sensitive information that can be abused if the signal processing is executed on remote servers or in the cloud. In this tutorial article, we introduce the fusion of signal processing and cryptography as an emerging paradigm to protect the privacy of users. While service providers cannot access directly the content of the encrypted signals, the data can still be processed in encrypted form to perform the required signal processing task. The solutions for processing encrypted data are designed using cryptographic primitives like homomorphic cryptosystems and secure multiparty computation. We include four boxes that provide introductory material on these cryptographic primitives. We first introduce encrypted signal processing for privacy protection using a toy example. We then discuss the application of cryptographic primitives to typical signal processing operations. Finally, we focus on prototypical solutions of increasing difficulty for privacy-preserving signal processing, namely privacy-preserving face recognition, secure clustering and content recommendation.

PrivacyProtectedSignalProcessing.pdf2.6 MB