Secure Multi-Party Computing

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Technically, (MPC) is different from homomorphic encryption, but it solves the same class of problems. In essence, MPC replaces the trusted third party with a protocol. This means that certain security properties, such as privacy and correctness, are preserved even if some participants collude and maliciously attack the protocol. In general, one can think of MPC as distributing cryptographic secrets piecemeal among all the computational participants. No one can decrypt the information, which may contain sensitive data, on their own. But all have access to the aggregated decrypted data. In practice, someone else can also perform the computation in such a way that the data analyst does not have access to the input data.

An example where this method can be useful is when greece whatsapp data have data that they are willing to provide to the government or some other organization for some purpose. But no one else should see the data. This happened when the city of Boston commissioned a local university to study the pay gap between men and women. The companies were willing to participate in the study, but for a variety of reasons they did not want to provide the figures in a form that others could see. Using MPC solved this problem.

Data is becoming increasingly important for optimizing companies’ operations and developing appropriate public policies. However, even with the best intentions (an assumption that is admittedly not always justified), sensitive information can leak out if the data is not handled properly.

And doing it right means going beyond historical rules of thumb and ad hoc approaches. While some methods are in various stages of development, it is increasingly important for data analysts to understand what new possibilities their existing toolboxes offer.