Research On Privacy-Preserving Multi-keyword Ranked Search Over Encrypted Cloud Data

With the emergence of cloud computing, more and more companies and individuals choose to store their data in the cloud. Cloud server reduces the burden of storage management on the user’s side, and allows the users to access data anywhere for high quality data storage services. With cloud storage mode, the user’s data needs to be outsourced to cloud server for storage and management. However, cloud is a third-party platform, and can easily access the data stored by the user. For the protection of data privacy, sensitive data has to be encrypted before outsourcing, which makes effective data utilization a challenging task. Thus, security problem becomes a fundamental problem which have hindered the development of cloud computing.In cloud computing, data owners may share their outsourced data with a large number of users, who might want to only retrieve certain specific data files they are interested in during a given session. One of the most popular ways is through keyword-based search. Such keyword search techniques allow users to selectively retrieve files of interest and have been widely applied in plaintext search. Unfortunately, data encryption, which restricts user’s ability to perform keyword search and further demands the protection of keyword privacy, makes the traditional plaintext search methods fail to encrypted cloud data. However, considering the large scale of data files stored in the cloud, it is not an efficient way to retrieve the specific files. If the encrypted data files couldn’t be searched and utilized easily, it violates the goal of data sharing in the cloud computing. Efficient search over encrypted data which has been an urgent problem needs to be addressed. Therefore, the study of search over encrypted cloud data is important.Existing techniques only support exact search, namely the search keyword should exactly match the words in the index. Some documents which contain semantically related words are ignored. For the reason that users has limited knowledge of some domain, the query keywords they provide are limited, which can’t fully express the actual query intent of users. Thus, the search results are incomplete. For the deficiencies, we have proposed two solutions which support semantic search over encrypted cloud data. The main contributions are described below.1) The paper introduces semantic search technology into the domain of ciphertext retrieval. When query keywords are submitted by data users, the scheme supports semantically search to make the results meet the need of users. This paper has proposed two semantic search schemes:one is an efficient and privacy-preserving semantic multi-keyword ranked search over encrypted cloud data, another is multi-keyword semantic ranked search over encrypted cloud data. These approaches support both the multi-keyword ranked search and the semantic search.2) For the protection of data privacy, before their data are submitted by data owners to the cloud server, the secure "k-nearest neighbor (k-NN)" is applied to split and transform their data. Even if the attacker obtains these data, these data are not the original data, so the data can be played a better protection. In the design process of scheme, we have discovered and proposed a new attack. We have conducted experiments to reveal the existence of this attack. And, it is proved that our proposed scheme can resist this attack effectively.