Advanced Security and Privacy in Cloud Computing: Enhancing Data Protection with Multikeyword Ranked Search in Encrypted Environments

Abstract

As cloud services become more popular, encryption becomes more important for user privacy. Establishing reliable solutions for secure and fast data retrieval is crucial. This research article proposes a novel way to search encrypted cloud data. The suggested method optimises queries with multiple terms and synonyms using a greedy depth-first search (DFS) algorithm and a sophisticated rating system. The suggested architecture assumes users would search using many keywords, some of which may be synonyms for article terms. A search algorithm that uses user query synonyms was created to solve this problem. Despite the constant increase of the search universe, greedy methods help us find the most relevant information. Our depth-first search strategy improves the likelihood of finding relevant information. Our study also uses a unique ranking system that considers keyword frequency, synonym precision, and keyword proximity to determine a text’s relevance to a search query. Our suggested methodology outperforms state-of-the-art methods in simulated cloud architecture experiments using encrypted datasets and industry-standard protocols. Runtime, accuracy, and recall show this superiority. The greedy Depth-First Search (DFS) algorithm optimises resources, improving efficiency. A grading method helps users quickly find the most relevant publications by naturally arranging the results. This synonym-enhanced search strategy in encrypted cloud storage systems may improve privacy and usability today.