Biblio

With cloud computing's development, more users are decide to store information on the cloud server. Owing to the cloud server's insecurity, many documents should be encrypted to avoid information leakage before being sent to the cloud. Nevertheless, it leads to the problem that plaintext search techniques can not be directly applied to the ciphertext search. In this case, many searchable encryption schemes based on single data owner model have been proposed. But, the actual situation is that users want to do research with encrypted documents originating from various data owners. This paper puts forward a privacy-preserving scheme that is based on fuzzy multi-keyword search (PPFMKS) for multiple data owners. For the sake of espousing fuzzy multi-keyword and accurate search, secure indexes on the basis of Locality-Sensitive Hashing (LSH) and Bloom Filter (BF)are established. To guarantee the search privacy under multiple data owners model, a new encryption method allowing that different data owners have diverse keys to encrypt files is proposed. This method also solves the high cost caused by inconvenience of key management.

The recent development of IoT technologies and cloud storages, many types of information including private information have been gradually outsourced. For such a situation, new convenient functionalities such as arithmetic and keyword search on ciphertexts are required to allow users to retrieve information without leaking any information. Especially, searchable encryptions have been paid much attention to realize a keyword search on an encrypted domain. In addition, an architecture of searchable symmetric encryption (SSE) is a suitable and efficient solution for data outsourcing. In this paper, we focus on an SSE scheme which employs a secure index for searching a keyword with optimal search time. In the conventional studies, it has been widely considered that the scheme searches whether a queried keyword is contained in encrypted documents. On the other hand, we additionally take into account the location of a queried keyword in documents by targeting a matrix-type data format. It enables a manager to search personal information listed per line or column in CSV-like format data.