Secure Error Correction using Multi-Party Computation
This addresses privacy-preserving data analysis for parties needing secure computation, but it is incremental as it builds on existing error-correcting methods.
The paper tackles the problem of errors in secure multi-party computation by proposing a technique to detect and correct errors on players' shares, based on Berlekamp-Welch error-correcting codes.
During recent years with the increase of data and data analysis needs, privacy preserving data analysis methods have become of great importance. Researchers have proposed different methods for this purpose. Secure multi-party computation is one of such techniques that allows a group of parties to evaluate a function on their data without revealing the data. This is done by secret sharing approach, in which parties share a piece of their data using polynomials and after doing function evaluation on shares of data finally they do a Lagrange interpolation to get the result. Two approaches have been proposed in secure multi-party computation for evaluating a function, arithmetic gates and logical gates. In both of them and since communication is an important step in multi-party computation, errors may happen. So, being able to detect and correct errors is important. Moreover, as adversaries may interrupt communication or manipulate the data, either in communication or during computation, this error detection and correction provide participating parties with a technique to detect such errors. Hence, in this paper we present a secure multi-party computation error correcting technique that has the ability to detect and correct errors on players shares. This technique is based on Berlekamp-Welch error correcting codes and we assume that players shares are generated using Reed-Solomon codes.