IGSK: Index Generation on Split Keyword for search over cloud data

Storage as a Service (Saas) of cloud computing has become an alternative option for data owners of various organizations to store their data into the cloud. Usually sensitive data is encrypted to achieve data security and then it is outsourced into cloud. Many traditional search schemes allow data user to search over encrypted cloud data through keywords and retrieve the files of interest selectively. In this paper, we propose an efficient approach for keyword search over encrypted cloud data. The main contribution of this paper involves index generation method for keywords by using split factor. The keywords are stored in wildcard based technique within the index tree that is stored securely with low storage cost. Extensive experimental results on real-time data sets shows that the proposed solution is effective as well as efficient in Index generation and storage cost

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

SoK: Cryptographically Protected Database Search

Protected database search systems cryptographically isolate the roles of reading from, writing to, and administering the database. This separation limits unnecessary administrator access and protects data in the case of system breaches. Since protected search was introduced in 2000, the area has grown rapidly; systems are offered by academia, start-ups, and established companies. However, there is no best protected search system or set of techniques. Design of such systems is a balancing act between security, functionality, performance, and usability. This challenge is made more difficult by ongoing database specialization, as some users will want the functionality of SQL, NoSQL, or NewSQL databases. This database evolution will continue, and the protected search community should be able to quickly provide functionality consistent with newly invented databases. At the same time, the community must accurately and clearly characterize the tradeoffs between different approaches. To address these challenges, we provide the following contributions: 1) An identification of the important primitive operations across database paradigms. We find there are a small number of base operations that can be used and combined to support a large number of database paradigms. 2) An evaluation of the current state of protected search systems in implementing these base operations. This evaluation describes the main approaches and tradeoffs for each base operation. Furthermore, it puts protected search in the context of unprotected search, identifying key gaps in functionality. 3) An analysis of attacks against protected search for different base queries. 4) A roadmap and tools for transforming a protected search system into a protected database, including an open-source performance evaluation platform and initial user opinions of protected search.Comment: 20 pages, to appear to IEEE Security and Privac

Efficient Fuzzy Search Engine with B-Tree Search Mechanism

Search engines play a vital role in day to day life on internet. People use search engines to find content on internet. Cloud computing is the computing concept in which data is stored and accessed with the help of a third party server called as cloud. Data is not stored locally on our machines and the softwares and information are provided to user if user demands for it. Search queries are the most important part in searching data on internet. A search query consists of one or more than one keywords. A search query is searched from the database for exact match, and the traditional searchable schemes do not tolerate minor typos and format inconsistencies, which happen quite frequently. This drawback makes the existing techniques unsuitable and they offer very low efficiency. In this paper, we will for the first time formulate the problem of effective fuzzy search by introducing tree search methodologies. We will explore the benefits of B trees in search mechanism and use them to have an efficient keyword search. We have taken into consideration the security analysis strictly so as to get a secure and privacy-preserving system.Comment: 5 pages, 6 figure

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

An efficient PHR service system supporting fuzzy keyword search and fine-grained access control

Outsourcing of personal health record (PHR) has attracted considerable interest recently. It can not only bring much convenience to patients, it also allows efficient sharing of medical information among researchers. As the medical data in PHR is sensitive, it has to be encrypted before outsourcing. To achieve fine-grained access control over the encrypted PHR data becomes a challenging problem. In this paper, we provide an affirmative solution to this problem. We propose a novel PHR service system which supports efficient searching and fine-grained access control for PHR data in a hybrid cloud environment, where a private cloud is used to assist the user to interact with the public cloud for processing PHR data. In our proposed solution, we make use of attribute-based encryption (ABE) technique to obtain fine-grained access control for PHR data. In order to protect the privacy of PHR owners, our ABE is anonymous. That is, it can hide the access policy information in ciphertexts. Meanwhile, our solution can also allow efficient fuzzy search over PHR data, which can greatly improve the system usability. We also provide security analysis to show that the proposed solution is secure and privacy-preserving. The experimental results demonstrate the efficiency of the proposed scheme.Peer ReviewedPostprint (author's final draft

Efficient Multi-User Keyword Search over Encrypted Data in Cloud Computing

As cloud computing becomes prevalent, more and more sensitive information are being centralized into the cloud. For the protection of data privacy, sensitive data usually have to be encrypted before outsourcing, which makes effective data utilization a very challenging task. In this paper, we propose a new method to enable effective fuzzy keyword search in a multi-user system over encrypted cloud data while maintaining keyword privacy. In this new system, differential searching privileges are supported, which is achieved with the technique of attribute-based encryption. Edit distance is utilized to quantify keywords similarity and develop fuzzy keyword search technique, which achieve optimized storage and representation overheads. We further propose a symbol-based trie-traverse searching scheme to improve the search efficiency. Through rigorous security analysis, we show that our proposed solution is secure and privacy-preserving, while correctly realizing the goal of fuzzy keyword search with multiple users