Abstract
Parallel computing offers the chance of improving the efficiency of Garbled Circuit technique in multi-party computation protocols. We propose two different types of parallelization: fine-grained, based on the parallel evaluation of gates, and coarse grained, based on the parallelization of macro-blocks. To analyze the efficiency of parallel implementation, a biometric scenario, having an intrinsically parallel nature, is considered. Moreover our approach is compared to previous works by using a privacy preserving implementation of AES encryption. We show that both fine-grained and coarse-grained solutions provide significant runtime improvements. Better results are obtained by the coarse-grained parallelization, which, however, can be exploited only when the same block is used more than once in parallel, whereas fine-grained parallelization can be applied to any garbled circuit.
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Notes
- 1.
Boolean circuit description kindly provided by Benny Pinkas, Thomas Schneider, Nigel P. Smart and Stephen C. Williams.
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Barni, M., Bernaschi, M., Lazzeretti, R., Pignata, T., Sabellico, A. (2014). Parallel Implementation of GC-Based MPC Protocols in the Semi-Honest Setting. In: Garcia-Alfaro, J., Lioudakis, G., Cuppens-Boulahia, N., Foley, S., Fitzgerald, W. (eds) Data Privacy Management and Autonomous Spontaneous Security. DPM SETOP 2013 2013. Lecture Notes in Computer Science(), vol 8247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54568-9_5
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