A Robust Fuzzy Based Multi-Keyword Similarity Search Model on Cloud Computing Platform Using Cipher Data Security Principles

In the era of cloud computing, secure data storage and retrieval have emerged as critical challenges due to the need to protect sensitive information while maintaining efficient access. This paper presents a robust fuzzy-based multi-keyword similarity search model that operates on encrypted cloud data, enhancing both security and performance. By combining fuzzy logic, homomorphic encryption, and multi-keyword search, this model offers improved accuracy in retrieving relevant documents based on user queries. The model achieves a search accuracy of 85% with two keywords, which increases progressively to 96.5% when 11 keywords are used. Additionally, the system demonstrates low encryption overhead, with encryption time scaling linearly as data size increases. The search time also remains efficient, growing from 50 ms for two keywords to 400 ms for 11 keywords. The model further enhances query efficiency, achieving 96% efficiency after processing 500 queries. The proposed solution addresses the growing need for secure and efficient cloud storage systems while ensuring user privacy. The results indicate the model's scalability, making it suitable for large datasets and high-volume cloud environments.