Split keyword fuzzy and synonym search over encrypted cloud data

A substitute solution for various organizations of data owners to store their data in the cloud using storage as a service(SaaS). The outsourced sensitive data is encrypted before uploading into the cloud to achieve data privacy. The encrypted data is search based on keywords and retrieve interested files by data user using a lot of traditional Search scheme. Existing search schemes supports exact keyword match or fuzzy keyword search, but synonym based multi-keyword search are not supported. In the real world scenario, cloud users may not know the exact keyword for searching and they might give synonym of the keyword as the input for search instead of exact or fuzzy keyword due to lack of appropriate knowledge of data. In this paper, we describe an efficient search approach for encrypted data called as Split Keyword Fuzzy and Synonym Search (SKFS). Multi-keyword ranked search with accurate keyword and Fuzzy search supports synonym queries are a major contribution of SKFS. The wildcard Technique is used to store the keywords securely within the index tree. Index tree helps to search faster, accurate and low storage cost. Extensive experimental results on real-time data sets shows, the proposed solution is effective and efficient for multi-keyword ranked search and synonym queries Fuzzy based search over encrypted cloud data. © 2017 Springer Science+Business Media, LL

Semantic Search over Encrypted Data in Cloud Computing

Cloud storage becomes more and more popular in the recent trend since it provides various benefits over the traditional storage solutions. Along with many benefits provided by cloud storage, many security problems arise in cloud storage which prevents enterprises from migrate their data to cloud storage. These security problems induce the data owners to encrypt all their sensitive data such as social security number (SSN), credit card information, and personal tax information before they can be stored in cloud storage. The encryption approach may have strengthened the data security of cloud data, but it degrades the data efficiency because the encryption reduces the searchability of the data. Many schemes were proposed in recent researches which enable keyword search over encrypted data in cloud computing, and these schemes contain weaknesses which make them impractical when applying these schemes in real-life scenarios. In this project, we developed a system to support semantic search over encrypted data in cloud computing with three different schemes. The three schemes that we developed are “Synonym-Based Keyword Search (SBKS)”, “Wikipedia-Based Keyword Search (WBKS)”, and “Wikipedia-Based Synonym Keyword Search (WBSKS)”. Based on our experiment data, it demonstrated that the indexes created by our schemes are 95% smaller and reduced the average search time by 95% if compared to the schemes proposed previously. These improvements illustrated that our developed schemes are more practical than the former proposed schemes

Semantic Search Approach in Cloud

With the approach of cloud computing, more and more information data are distributed to the public cloud for economic savings and ease of access. But, the encryption of privacy information is necessary to guarantee the security. Now a days efficient data utilization, and search over encrypted cloud data has been a great challenge. Solution of existing methods depends only on the keyword of submitted query and didn�t examine the semantics of keyword. Thus the search schemes are not intelligent and also omit some semantically related documents. To overcome this problem, we propose a semantic expansion based similar search solution over encrypted cloud data. The solution of this method will return not only the exactly matched files, but also the files including the terms semantically related to the query keyword. In this scheme, a corresponding file metadata is constructed for each file. After this, both the encrypted file metadata set and file collection are uploaded to the cloud server. With the help of metadata set file, the cloud server maintains the inverted index and create semantic relationship library (SRL) for the keywords set. After receiving a query request from user , this server firstly search out the keywords that are related to the query keyword according to SRL. After this, both the query keyword and the extensional words are used to retrieve the files to fulfill the user request. These files are returned in order according to the total relevance score. Our detailed security analysis shows that our method is privacy-preserving and secure than the previous searchable symmetric encryption (SSE) security definition. Experimental evaluation demonstrates the efficiency and effectives of the scheme