STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Data Obfuscation: Anonymity and Desensitization of Usable Data Sets
IEEE Security and Privacy
Privacy preserving error resilient dna searching through oblivious automata
Proceedings of the 14th ACM conference on Computer and communications security
Improved Garbled Circuit: Free XOR Gates and Applications
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part II
Fully homomorphic encryption using ideal lattices
Proceedings of the forty-first annual ACM symposium on Theory of computing
Privacy-Preserving Face Recognition
PETS '09 Proceedings of the 9th International Symposium on Privacy Enhancing Technologies
Secure evaluation of private linear branching programs with medical applications
ESORICS'09 Proceedings of the 14th European conference on Research in computer security
IEEE Transactions on Information Forensics and Security
Twin clouds: secure cloud computing with low latency
CMS'11 Proceedings of the 12th IFIP TC 6/TC 11 international conference on Communications and multimedia security
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Signal processing governs almost every audiovisual stimuli that we receive from electronic sources. Recently, concerns about privacy of the processed signals (especially biomedical signals) has been raised, as it has been traditionally overlooked. This fact, together with the advent of Cloud computing and the growing tendency to outsource not only the storage but also the processing of data has created a fundamental need for privacy preserving techniques that protect signals at the Cloud. We provide a landscape of technologies brought up by the novel discipline of Signal Processing in the Encrypted Domain (SPED), and we show their application to solve Cloud Computing privacy issues, introducing the concept of virtualized CryptoDSPs, as an architecture for implementing SPED technologies on Cloud scenarios.