Machine Learning

Acompany releases an open source software QuickMPC

Acompany today announced that it has released as open source software QuickMPC, a practical engine for Secure Multiparty Computation (SMPC) that is part of privacy-enhancing computation (PEC). This is the first client-server SMPC OSS in the world. QuickMPC can perform computations on personal data used in fundamental static calculations and machine learning while keeping confidentiality. This will enable businesses and engineers worldwide to use Python and JavaScript (TypeScript) client libraries to easily develop SaaS products that utilize SMPC functions without the need for expert SMPC knowledge.

Acompany PEC software is available as an open-source on GitHub here (https://github.com/acompany-develop/QuickMPC).

Data protection is a key issue. As a result of laws such as GDPR and CCPA that protect personal data, heretofore unregulated data utilization has become more difficult. In addition, Gartner is predicting that by 2025, 60% of large organizations will use at least one PEC technique in analytics, business intelligence and/or cloud computing.

Acompany is a startup founded in 2018 by student entrepreneurs. The company arrived upon SMPC after being involved in blockchain technology. At the time, practical level open source SMPC did not exist, so the company set upon independently developing QuickMPC. Now, the company has released the QuickMPC engine and two client libraries. Acompany CTO Takeharu Kondo comments on the release, “Back in 2019, most open source software of secure computing engines was mainly for researchers. So we successfully developed QuickMPC independently. Now we have released it as open source software.”

Within the next few years, Acompany will spread PEC from Japan to the rest of the world.

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