А MACHINE LEARNING MODEL BASED ON HETEROGENEOUS DATA

Narbayeva S.M. Tapeeva S.K. Turarbek A. Zhunusbayeva S.
2022 al-Farabi Kazakh State National University

KazNU Bulletin. Mathematics, Mechanics, Computer Science Series
2022 #114 Issue 2 80 - 90 pp.

Big data is widely used in many areas of business. The information between organizations is systematically reproduced and processed by data, and the collected data differs significantly in attributes. By composing heterogeneous data sets, they complement each other, therefore, data exchange between organizations is necessary. In a machine learning collaborative learning process based on heterogeneous data, the current schema has many challenges, including efficiency, security, and availability in real-world situations. In this paper, we propose a secure SVM learning mechanism based on the consortium blockchain and a threshold homomorphic encryption algorithm. By implementing the consortium’s blockchain, it is possible to build a decentralized data exchange platform, and also to develop a secure algorithm for the support-vector machine classifier based on threshold homomorphic encryption.

Blockchain , heterogeneous data , secure scheme , SVM

Text of the article Перейти на текст статьи

Al-Farabi Kazakh National University, Almaty, Kazakhstan

Al-Farabi Kazakh National University

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026