Graph-Based Algorithms for Boolean Function Manipulation
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Privacy-preserving protocols allow multiple parties with private inputs to perform joint computation while preserving the privacy of their respective inputs. An important cryptographic primitive for designing privacy-preserving protocols is secure function evaluation (SFE). The classic solution for SFE by Yao uses a gate representation of the function that the two parties want to jointly compute. Fairplay is a system that implements the classic solution for SFE. In this paper, we present a new protocol for SFE that uses a graph-based representation of the function. Specifically we use the graph-based representation called ordered binary decision diagrams (OBDDs). For a large number of Boolean functions, OBDDs are more succinct than the gate-based representation. Preliminary experimental results based on a prototype implementation shows that for several functions, our protocol results in a smaller bandwidth than Fairplay. For example, for the classic millionaire's problem, our new protocol results in a approximately $45$\% bandwidth reduction over Fairplay. Therefore, our protocols will be particularly useful for applications for environments with limited bandwidth, such as applications for wireless and sensor networks.