Semantic-Aware Efficient Multi-Keyword Top K-Similarity Search Over Encrypted Cloud Data

Abstract

Outsourcing data storage in infrastructure has been a popular solution for organizations and individual users since it offers numerous advantages over traditional on-premises storage choices. Data encryption before outsourcing data to infrastructure is a general strategy to safeguard data confidentiality. It is challenging to search for the specified keywords in encrypted datasets in cloud computing settings, and it is obviously impracticable to download all the data from the cloud and decode it locally. The focus of current search technique is on exact matches and simple pattern matching, which result in incomplete or irrelevant. The approach uses 4D hyperchaotic mapping and a powerful deoxyribonucleic acid (DNA) encryption mechanism to make it very difficult to decrypt the encrypted data without the proper key. The proposed approach helps create an effective and safe encryption. Global vector word embedding is taken into consideration while generating semantically aware search results in a semantically conscious top-k multi-keyword retrieval-supporting searchable encryption technique.