분산 학습으로의 적용을 위한 극소 부호의 확장 기법

Abstract

Recently, various artificial intelligence technologies are being applied to smart factory, finance, healthcare, and so on. When handling data requiring protection of privacy, distributed learning techniques are used. For distribution of information with privacy protection, encoding private information is required. Minimal codes has been used in such a secret-sharing scheme. In this paper, we explain the relationship between the characteristics of the minimal codes for application in distributed systems. We briefly deals with previously known construction methods, and presents extension methods for minimal codes. The new codes provide flexibility in distribution of private information. Furthermore, we discuss application scenarios for the extended codes.