Efficient oblivious transfer protocols
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Precomputing Oblivious Transfer
CRYPTO '95 Proceedings of the 15th Annual International Cryptology Conference on Advances in Cryptology
Priced Oblivious Transfer: How to Sell Digital Goods
EUROCRYPT '01 Proceedings of the International Conference on the Theory and Application of Cryptographic Techniques: Advances in Cryptology
PKC '01 Proceedings of the 4th International Workshop on Practice and Theory in Public Key Cryptography: Public Key Cryptography
Fairplay—a secure two-party computation system
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
Privacy-preserving remote diagnostics
Proceedings of the 14th ACM conference on Computer and communications security
How to generate and exchange secrets
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
Improved Garbled Circuit: Free XOR Gates and Applications
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part II
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
Fair secure two-party computation
EUROCRYPT'03 Proceedings of the 22nd international conference on Theory and applications of cryptographic techniques
Composite signal representation for fast and storage-efficient processing of encrypted signals
IEEE Transactions on Information Forensics and Security
Privacy-Preserving ECG Classification With Branching Programs and Neural Networks
IEEE Transactions on Information Forensics and Security
Division between encrypted integers by means of Garbled Circuits
WIFS '11 Proceedings of the 2011 IEEE International Workshop on Information Forensics and Security
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Remote health-care applications are gaining popularity as an alternative for patients who do not require hospitalization. In this setting, privacy preserving protocols are useful to enable the offering of personalized online services, thus preventing the unnecessary disclosure of personal data. A problem often neglected in privacy-preserving protocols is the need to ensure that processed signals, which are often recorded by non-expert consumers, are of sufficient quality, hence raising the need for solutions that assess the quality of the recorded signals to guarantee correct (medical) decisions. In this paper, we propose a privacy preserving protocol that assesses signal quality and combines this with a linear classifier used to decide whether the measured signal is of high enough quality or not. In particular, the protocol computes a frame based Signal-To-Noise Ratio (SNR) from the original signal and a filtered version of the signal itself; evaluates the mean and the variance of the SNRs obtained and computes the overall signal SNR. Finally these measures are combined with a linear classifier used to assess the quality of the signal. The proposed scheme relies on a hybrid multi-party computation protocol based on Homomorphic Encryption and Yao's Garbled Circuits. The analysis of the protocol indicates that it needs the transmission of less than 4~MBytes of data to analyze 30 seconds of ECG signals providing a classification accuracy close to 85%.