Secure Evaluation of Private Linear Branching Programs with Medical Applications
| Autor: | Pierluigi Failla, Ahmad-Reza Sadeghi, Mauro Barni, Thomas Schneider, Riccardo Lazzeretti, Vladimir Kolesnikov |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2009 |
| Předmět: |
021110 strategic
defence & security studies Oblivious transfer Signal Processing in the encrypted domain business.industry Computer science 0211 other engineering and technologies homomorphic encryption garbled circuits Homomorphic encryption homomorphic encryption garbled circuits 02 engineering and technology Benchmarking Remote evaluation Service provider computer.software_genre Statistical classification Health care 0202 electrical engineering electronic engineering information engineering Diagnostic program 020201 artificial intelligence & image processing Data mining business computer |
| Zdroj: | Computer Security – ESORICS 2009 ISBN: 9783642044434 ESORICS |
| Popis: | Diagnostic and classification algorithms play an important role in data analysis, with applications in areas such as health care, fault diagnostics, or benchmarking. Branching programs (BP) is a popular representation model for describing the underlying classification/diagnostics algorithms. Typical application scenarios involve a client who provides data and a service provider (server) whose diagnostic program is run on client's data. Both parties need to keep their inputs private. We present new, more efficient privacy-protecting protocols for remote evaluation of such classification/diagnostic programs. In addition to efficiency improvements, we generalize previous solutions - we securely evaluate private linear branching programs (LBP), a useful generalization of BP that we introduce. We show practicality of our solutions: we apply our protocols to the privacy-preserving classification of medical ElectroCardioGram (ECG) signals and present implementation results. Finally, we discover and fix a subtle security weakness of the most recent remote diagnostic proposal, which allowed malicious clients to learn partial information about the program. |
| Databáze: | OpenAIRE |
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