Semantic based multi lexical ranking technique for an effective search in protected cloud

With the hasty popularity of cloud computing data possessor are stimulated to move their intricate data from local repository to commercially available open cloud. We need to search and retrieve all the files which are semantically linked to the query in addition to the precise identical file in a secured manner. But for protecting sensitive information like military information, personal health documents etc, these documents have to be shielded before moving to cloud; which prevents conventional search methodologies using plain text keyword search. It is essential to use multi k-words in searching and retrieve the documents based on their significance order of k-word by considering the ever rising number of data possessor and documents in cloud. Meanwhile existing approaches only support fuzzy keyword based search but not semantic based search. There are works based on multi keyword ranked search using synonymous queries but not based on semantics. For securing the data in the cloud, we use (Advanced Encryption Standard) AES algorithm to encrypt the data and (Reverse Advanced Encryption Standard) RAES to decrypt the same. We use secured (k-Nearest Neighbour) KNN algorithm to achieve secured search. In order to provide semantic based search we include a tool called wordnet where we perform semantic based analysis of the files and then include secured KNN over the documents and rank them according to their order of relevance primarily using the term and inverse document frequency.