Semantic key generation based on natural language

In recent years, the public has become more aware of security concerns, and the demand for convenient and efficient encryption technology has increased. Biological data is used in identity authentication and key generation as the innate characteristic information of people. Biological key have the advantage of convenience and fast application without carrying any document; however, they also have the disadvantage of biological characteristic leaks and the inability to change. Based on the advantages and disadvantages of biological key, we propose the concept of semantic key. Language, a medium that fills the lives of people, has similar characteristics of convenience and fast application as biological key; however, semantic key will not reveal biological information. As the amount of semantic information is large, it can be changed at any time. Compared with biological key, it provides better security and flexibility. Therefore, we propose a semantic key generation framework of semantic extraction + feature stabilization + fuzzy extraction that improves the existing semantic extraction model and feature stabilization model and design the semantic key extraction model. In terms of artificial sentence formation, semantic key can be extracted with an accuracy of more than 99%, and an error rate of less than 0.5%.