Improved Building Blocks for Secure Multi-party Computation Based on Secret Sharing with Honest Majority
| Autor: | Ah Reum Kang, Chen Yuan, Marina Blanton |
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| Rok vydání: | 2020 |
| Předmět: |
050101 languages & linguistics
Focus (computing) Computer science Computation media_common.quotation_subject 05 social sciences 02 engineering and technology Computer security model Computer security computer.software_genre Secret sharing Popularity Reading (process) 0202 electrical engineering electronic engineering information engineering Secure multi-party computation 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences Multiplication computer media_common |
| Zdroj: | Applied Cryptography and Network Security ISBN: 9783030578077 ACNS (1) |
| DOI: | 10.1007/978-3-030-57808-4_19 |
| Popis: | Secure multi-party computation permits evaluation of any desired functionality on private data without disclosing the data to the participants. It is gaining its popularity due to increasing collection of user, customer, or patient data and the need to analyze data sets distributed across different organizations without disclosing them. Because adoption of secure computation techniques depends on their performance in practice, it is important to continue improving their performance. In this work, we focus on common non-trivial operations used by many types of programs, where any advances in their performance would impact the runtime of programs that rely on them. In particular, we treat the operation of reading or writing an element of an array at a private location and integer multiplication. The focus of this work is on secret sharing setting with honest majority in the semi-honest security model. We demonstrate improvement of the proposed techniques over prior constructions via analytical and empirical evaluation. |
| Databáze: | OpenAIRE |
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