Knowledge inference for optimizing secure multi-party computation
Aseem Rastogi, Piotr Mardziel, Michael Hicks, Matthew A. Hammer · 2013
In secure multi-party computation, mutually distrusting parties cooperatively compute functions of their private data; in the process, they only learn certain results as per the protocol (e.g., the final output). The realization of these protocols uses cryptographic techniques to avoid leaking information between the parties. A protocol for a secure computation can sometimes be optimized without changing its security guarantee: when the parties can use their private data and the revealed output to infer the values of other data, then this other data need not be concealed from them via cryptography.