セキュアマルチパーティ計算（SMPC）
Secure Multi-Party Computation (SMPC) is a cryptographic protocol that enables multiple parties to jointly compute a function over their inputs while ensuring that those inputs remain private. This technology is particularly useful in scenarios where sensitive data needs to be processed collaboratively, such as in finance, healthcare, and データ分析.
一般的なSMPCの設定では、各参加者は秘密のデータの一部を保持し、自分のデータを他者に明かすことなく、すべての入力に依存する結果を計算したいと考えています。プロトコルは、入力データをシェアに分割し、それを参加者間で配布します。各参加者は自分のシェアに対して独立して計算を行い、最終的な結果だけが参加者間で共有されます。これにより、個々の参加者は完全な情報にアクセスできません。
There are several techniques used in SMPC, including additive sharing, multiplicative sharing, and ホモモルフィック暗号, each with its own advantages and application contexts. For example, additive sharing allows parties to sum their inputs without revealing them, while homomorphic encryption allows computations to be performed directly on encrypted data.
SMPC is gaining traction in various industries, particularly in privacy-preserving 機械学習, where models can be trained on distributed data without exposing the underlying datasets. As data privacy concerns grow, the importance of SMPC in enabling secure collaboration will likely increase.