Research On Privacy Preserving Searchable Encryption Technology In Cloud Computing Environment

As Cloud Computing becomes prevalent, more and more data owners prefer to store their local data into the cloud. In order to protect the data security and user privacy, sensitive data usually has to be encrypted before outsourcing, which makes effective data utilization a challenging task. In other words, the challenge lies in how the users can retrieve data files they are interested in over the encrypted cloud data without decrypting them first.Searchable encryption techniques in the cloud environment generally first build up an index for each keyword, and then outsource the encrypted indices and data files to the cloud server. Users can securely retrieve their interested data files through inputting encrypted keyword. However, these techniques neither allow spelling errors and format inconsistencies, nor capture the relevance among data files and return the files in a ranked order. Furthermore, these techniques support only the single-keyword search. Although privacy preserving fuzzy keyword search schemes and ranked keyword search schemes over encrypted cloud data have been developed in recent years, these schemes function unilaterally, without considering various problems that may occur during the retrieval process. Besides, the large index-table size of the existing fuzzy keyword search schemes over encrypted cloud data requires a large storage space, which greatly reduces the system usability and retrieval efficiency. Thus, how to reduce the index-table size and how to incorporate fuzzy keyword search with ranked keyword search have become two hot topics in searchable encryption in the cloud computing environment.In this thesis, we first summarize the theoretical basis and some relevant mainstream techniques of privacy preserving searchable encryption in cloud computing environment, and then introduce some existing fuzzy keyword search algorithms and ranked keyword search algorithms over encrypted cloud data respectively. On this basis, we present a privacy preserving searchable encryption algorithm that supports both fuzzy keyword search and ranked keyword search, and a k-gram based privacy preserving ranked fuzzy keyword search algorithm over the encrypted cloud data that support multiple keywords search, respectively.The main work of the thesis is summarized below:1. Current privacy preserving searchable encryption techniques in the cloud are analyzed. In order to deal with the drawbacks of traditional searchable encryption techniques, by incorporating the current privacy preserving fuzzy keyword search algorithms and secure ranked keyword search algorithms over encrypted cloud data, we build a new indexing structure and propose a privacy preserving keyword search algorithm over encrypted cloud data that supports both fuzzy keyword search and ranked keyword search. The experimental results show that the algorithm can securely and effectively support the two mainstream techniques mentioned above.2. Based on the k-gram indexing algorithm in the plaintext information retrieval field and the first work mentioned above, we use Jaccard coefficient to quantify string similarity and construct fuzzy keyword set, and propose a privacy preserving ranked fuzzy keyword search algorithm that supports multi-keyword search over encrypted cloud data in addition to fuzzy keyword search and ranked keyword search. The complexity analysis and experimental results show that the proposed algorithm has an index table of smaller size, and users can securely and effectively retrieve files of interest over encrypted cloud data.