An efficient approach secret key for multi-keyword ranked search over encrypted cloud data

Abstract

Data mining focuses on generating a useful knowledge from the data sources rather than a mere data extracting technology. As increasing popularity of cloud computing, more and more data owners are motivated to their data to cloud servers for great convenience and reduced cost in data management. So, sensitive data should be encrypted before outsourcing for, privacy requirements, which obsoletes data utilization like keyword- based document retrieval. A secret key generation for multi-keyword ranked search over encrypted cloud data, which simultaneously dynamic update operations like modify and view of documents. Specifically, the vector space model and the widely-used TF IDF model are combined in the index construction and query generation. The secure kNN algorithm is utilized to encrypt the index and query vectors, and mean while ensure correct relevance score calculation between encrypted index and query vectors. In order to provide security, the secrete key is generated for each data owners individual electronic mail. That secrete key can be copied and pasted for further login. When the user wants to change their password the secret key also been updated.