A NFT verification method for distributed AI system

Autor:	Tong Zhang, Mingyan Song, Yue Sui, Hanlin Chen, Jian Tan
Rok vydání:	2021
Předmět:	History Computer Science Applications Education
Zdroj:	Journal of Physics: Conference Series. 2132:012017
ISSN:	1742-6596 1742-6588
Popis:	This paper proposes a method invention, namely an efficient NFT data inspection method with minimum granularity and probability comparison. The invention establishes a fast comparison method of AI model and data, that is, the direct comparison of small files priority and the maximum-minimum interval comparison. The invention takes the substantial identity inside the NFT data and the processing method of NFT data coincidence into account, so that the data content outside the token of the NFT publicly shared by the AI distributed system can also be unique on the Internet. Therefore, it can avoid the problem of incremental packaging and repeated packaging, and can successfully balance the efficiency and security of the comparison process. portions given in this document
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::eddb64f161e4fe25c955282ed0da8b48 https://doi.org/10.1088/1742-6596/2132/1/012017 Zobrazit plný text záznamu