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 seminar I will first discuss the problems, principles and examples of protecting the privacy of users in multimedia applications. I then introduce the fusion of signal processing and cryptography as an emerging paradigm to protect the privacy of users . This new and exciting research area of privacy-preserving signal processing aims at making privacy-sensitive data of the user of such multimedia applications inaccessible by means of encryption. 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.

The seminar gives an overview of a number of relevant privacy-preserving signal processing cases and related security requirements. Typical signal processing operations such as linear transforms will be discussed briefly. Next the prototypical cryptographic protocols will be introduced in the context of the signal processing operations. These protocols include blinding, multi-party computation, and homomorphic crypto systems. I then describe a number of examples that show solutions for privacy-preserving signal processing, including privacy-preserving face recognition and secure clustering.Several open issues in “designing privacy in signal processing” are finally presented for further discussion.