Leveraging the "Multi" in secure multi-party computation
Jaideep S. Vaidya, Chris Clifton
Abstract
Jaideep S. Vaidya, Chris Clifton
Abstract
Secure Multi-Party Computation enables parties with private data to collaboratively compute a global function of their private data, without revealing that data. The increase in sensitive data on networked computers, along with improved ability to integrate and utilize that data, make the time ripe for practical secure multi-party computation. This paper surveys approaches to secure multi-party computation, and gives a method whereby an efficient protocol for two parties using an untrusted third party can be used to construct an efficient peer-to-peer secure multi-party protocol.
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Secure Multi-Party Computation enables parties with private data to collaboratively compute a global function of their private data, without revealing that data. The increase in sensitive data on networked computers, along with improved ability to integrate and utilize that data, make the time ripe for practical secure multi-party computation. This paper surveys approaches to secure multi-party computation, and gives a method whereby an efficient protocol for two parties using an untrusted third party can be used to construct an efficient peer-to-peer secure multi-party protocol.
Key concepts: Secure two-party computation, Computer science, Secure multi-party computation, Computation, Construct (python library), Protocol (science), Trusted third party, Third party