In the last years, we have witnessed the coincidence of several key factors, such as the popularization of social networks and the creation of multiple web services that store and process personal data in environments out of the control of the data owner. This fact raised the issue of personal data privacy, therefore questioning the legality and morality of the use of such data by untrustworthy parties. Furthermore, European data protection directives require a high level of privacy protection for personal and sensitive data in virtually any context.

The emergent discipline of Signal Processing in the Encrypted Domain (SPED), born as a result of the joint efforts of the cryptographic community and signal processing community, provides efficient technological means to enforce privacy protection in signal processing applications. This target is achieved through the development of malleable encryption schemes and secure protocols for sensitive data and signals that allow for the execution of operations directly on the encrypted signals, with no access to them in the clear. Hence, the application of SPED techniques preserves users' privacy even when their data are stored and processed in an untrusted environment, like a public Cloud.

The GPSC has an active research line in SPED, with a broad theoretical-practical scope, that has been materialized in recent years in numerous publications and contributions to international journals and conferences, and several international patent applications in the area of secure signal processing. The privacy models and primitives developed within the GPSC build upon cryptographic concepts like Secure Multiparty Computation and Secure Function Evaluation. However, we have not left aside the practical approach given by the numerous applications of this technology, some of them being

• Protection of biometric signals in access control systems
• Secure adaptive filtering
• Privacy protection in outsourced multimedia Clouds
• Privacy protection in videosurveillance systems
• Privacy in fine-grained Smart Metering applications
• Data mining on private databases
• Secure applications for eHealth (telediagnosis/telemedicine, e.g., DNA analysis)
• Traceability of copyright infringements through private insertion of watermarks