Anonymously Multiple Keyword Ranking Search Over Encrypted Data In Cloud Computing

With the rapid development of cloud computing technology, more and more enterprises or individuals upload their private data to store on the cloud servers. However, while enjoying convenient and quick cloud storage services, users are increasingly concerned about the security and reliability of their data in the cloud. In order to ensure their data privacy, data owners encrypt the plaintext before data communication with the cloud server. Nevertheless, with this approach, it is extremely difficult for users to manage their cloud data, especially for keyword search for ciphertext.Now there are still several disadvantages in the existing schemes of keyword search for ciphertext, such as lower efficiency, lower security or they do not support the similarity sort of search results and their file indexes can’t be updated dynamically. This thesis presents an efficient scheme for anonymously multiple keyword ranking search over encrypted data in cloud computing. Firstly, the system model of this scheme is designed to be applicable to search for ciphertext in cloud, with four entities such as data owner, authorized user, CSP and trusted third party (TTP). Thereinto, TTP is responsible for encrypting users’ index vectors and transmitting the communication information between users and CSP, which achieves anonymous searches. In addition, this thesis introduces Counting Bloom filter to structure index vectors, so that the search efficiency can be improved. Accordingly, file index vectors import term frequency, while search vectors generated by users import term weight, which realizes based on users’custom searches and makes results more accurate. By using KNN algorithm to encrypt index vectors, the index security can be guaranteed. When an authorized user searches, CSP computes the similarity of inner product between encrypted file index vectors and search vectors and sorts by score. Finally, the search results are passed to authorized users through TTP.At last, through the simulation experiments, the results show that the proposed scheme is superior to MRSE in many aspects, such as the generating time of encrypted file index vectors, the execution efficiency of score algorithm and the accuracy of search results. Therefore, on the foundation of ensuring the security and privacy of cloud data, this scheme can achieve efficient and precise multiple keyword ranking search function.