Blockchain data privacy text intelligent encryption method based on machine learning and symbolic computing in the context of metaverse

Abstract

To understand the blockchain data privacy text intelligent encryption method based on machine learning and symbolic computing, the author proposes research on the blockchain data privacy text intelligent encryption method based on machine learning and symbolic computing under the background of Metaverse. First, according to the requirements and standards of text encryption, the author preprocesses the blockchain text intelligent encryption environment, sets the grid big data encryption goal, and integrates big data technology on this basis, build a multi-level intelligent text encryption structure, gradually expand the scope of encryption, break the overall restrictions, and build a blockchain private text big data intelligent encryption model. Secondly, big data text conversion correction is used to implement encryption processing for testing. After encrypting the text, select four transmission channels to ensure their environment is consistent, and set the transmission and reception location points. Integrate big data technology, establish a visual encryption processing space, put the transmission measurement time to 3 min, 6 min, 9 min, and 10 min respectively, and design a targeted transmission attack program in the test platform as an auxiliary test program. Finally, the test results show that the big data blockchain private text encryption test group finally obtains relatively high anti-attack times, indicating that the encryption effect of this method is better, and the security of private text is higher, which has greater practical application value.