Abstract: The relevance a lot of keywords will change a lot of precise came results, and therefore the preference factors of keywords represent the importance of keywords within the search keyword set nominative by search users and correspondingly permits personalized search to cater to specific user preferences. Individual will remotely store her knowledge on the cloud server, specifically knowledge outsourcing, and so create the cloud knowledge open for public access through the cloud server. It contain sensitive privacy info, they're usually encrypted before uploaded to the cloud. However, considerably limits the usability of outsourced knowledge thanks to the issue of looking out over the encrypted knowledge. during this paper, we tend to address this issue by developing the fine-grained multi-keyword search schemes over encrypted cloud knowledge. The cloud server then uses the cipher text to match the outsourced encrypted keywords, and in conclusion returns the matching results to the search user. to attain the similar search potency and exactitude over encrypted knowledge as that of plaintext keyword search, an in depth body of analysis has been developed in literature. an exploration user queries the outsourced documents from the cloud server with following 3 steps. First, the search user receives each the key key and symmetrical key from the information owner. Second, in line with the search keywords, the search user uses the key key to come up with trapdoor and sends it to the cloud server. Last, she receives the matching document assortment from the cloud server and decrypts them with the symmetrical key.