Application of cryptography in data privacy using fuzzy graph theory

Abstract

While exchanging data across different companies, data privacy has become very essential in fuzzy graph theory. Many fuzzy graph theory facilities, include fuzzy logic as plain text transmission, which in turn causes data breach. When sensitive data has to be encrypted, we employ membership functions with varying degrees of fuzzy graph theory. Once our algorithm has finished running, we utilize an auto cryptography encoder to transmit the altered data. After creating the auto cryptography encoder, various organizations may utilize the output data for research analysis as well as for productivity analysis by deploying it in live data environment. Data that has been stored is used by other fuzzy graph theory entities or research analysts to enhance the well-being of individuals. The fuzzy data, however, include various lattice structures to resolve complex problems. Data privacy is put at the risk if sensitive data is revealed. The study that has ensued as a result of this discovery has spurred several privacy-preserving methods to be developed. So, we created a method that encrypts critical information using cryptography technique and, moreover, securely transmits data to many companies.