Accelerating Multiparty Computation by Efficient Random Number Bitwise-Sharing Protocols
It is becoming more and more important to make use of personal or classified information while keeping it confidential. A promising tool for meeting this challenge is multiparty computation (MPC), which enables multiple parties, each given a snippet of a secret s, to compute a function f(s) by communicating with each other without revealing s. However, one of the biggest problems with MPC is that it requires a vast amount of communication and thus a vast amount of processing time. We analyzed existing MPC protocols and found that the random number bitwise-sharing protocol used by many of them is notably inefficient. We proposed efficient random number bitwise-sharing protocols, dubbed ‘‘Extended-Range I and II,” by devising a representation of the truth values that reduces the communication complexity to approximately 1/6th that of the best of the existing such protocol. We reduced the communication complexity to approximately 1/26th by reducing the abort probability, thereby making previously necessary backup computation unnecessary. Using our improved protocols, ‘‘Lightweight Extended-Range II,” we reduced the communication complexities of equality testing, comparison, interval testing, and bit-decomposition, all of which use the random number bitwise-sharing protocol, by approximately 91, 79, 67, and 23% (for 32-bit data) respectively. Our protocols are fundamental to sharing random number r ∈ ℤ p in binary form and can be applicable to other higher level protocols
KeywordsRandom Number Secret Sharing Communication Complexity Equality Testing Binary Form
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