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Broadcast Searchable Keywords Encryption (BSKE) is a novel scheme that allows searching in encrypted data without knowing a secret key. Consider Bob wants to encrypt the same data under master public key for a group of users and stores this encrypted data with Alice, Malice is one of those recipients he asks Alice
encryption is a cryptographic primitive allowing for private keyword based search over the encrypted database. The above setting of enterprise outsourcing database to the cloud requires multi-user searchable encryption, whereas virtually all of the existing schemes consider the single-user setting. To bridge this gap, we are
Efficient multi-keyword fuzzy search over encrypted data is a desirable technology for data outsourcing in cloud storage. The current solutions can only support part of these goals. In this paper, we propose a novel encrypted data searching scheme that can support multiples keywords fuzzy search with high efficiency
makes effective data utilization a challenging task. Traditional data utilization based keyword search on encrypted data is a difficult task. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in the cloud, it is necessary to allow
Searchable encryption is crucial for the encrypted data utilization, especially in the database generated by multiple owners. Many existing schemes support single keyword query, and assume that the search users are authorized and the returned results are correct. However, single keyword query wastes network bandwidth
Fuzzy keyword search is an important and necessary functionality for information retrieval in modern cloud storage services, since cloud users may submit queries with typos errors or have deficient knowledge about the underlying keywords of cloud data sets. However, for the purpose of privacy preservation, data is
is very different from the retrieval of plaintext. The traditional plaintext retrieval method is no longer suitable for the retrieval of the cipher text. In the previous fuzzy search strategy, although fuzzy keyword sets that building on keyword dictionary can realize the fuzzy search. But when the keyword set is
Public key encryption with keyword search applies only to the certain circumstances that keyword ciphertext can only be retrieved by a specific user and only supports single-keyword matching. In the existing searchable encryption schemes, either the communication mode is one-to-one, or only single-keyword search is
There exists a specific security issue in symmetric searchable encryption that, when doing CKS(Conjunctive Keywords Search), the trapdoors and search results may reveal the relationships between the keywords being searched. For example, if the search result of keywords set A is the superset of keywords set B's, it
directly. Regular encryption algorithms such as AES, RC4 and DES mechanisms have searching limitation, in which the whole ciphertext needs to be retrieved and then decrypt before search procedure can be performed. Recently a lot of research has been done to enable search capabilities for users. Generally, keyword based search
without decrypting the ciphertext or the searching keywords. In this paper, we propose a construction which can dramatically reduce the size of extra storage in the searchable symmetric encryption schemes and still remain efficiency. And security analysis shows that our construction can achieve non-adaptive secure. Further
OpenEHR is an open standard specification for developing flexible electronic health record (EHR) management system. It defines the standard service models and APIs, and offers a whole lifetime data storage method to the patient's record. As an important OpenEHR system component, EHRServer plays the role of back-end services repository for data storage and query. It complies with the openEHR specifications...
digital signature — in an integrated, embedded, and fine-grained manner, based on open standards such as eXtensible Access Control Markup Language, XML Encryption, XML Signature, and XML Key Management Specification. To support patient-controlled encryption and privacy-preserving keyword search, we use ciphertext
Public key encryption scheme with keyword searchable (PEKS) enables one to search for encrypted keywords without compromising the confidentiality of the original data. A practical PEKS scheme should have the following properties: quickly and efficiently searchable method, ciphertext integrity, a small amount of
-efficiency and privacy. Three secure search protocols, namely Ostrovsky protocol, COPS protocol and EIRQ protocol are discussed in this paper. Each of these protocols incrementally improves upon the basic keyword search. Ostrovsky protocol offers privacy. COPS protocol aggregates the search results and achieves cost efficiency
, which will allow them to utilize cloud services without the risks of leaking private data to outsiders and even service providers. In this paper, we propose an exclusive-or (XOR) homomorphism encryption scheme to support secure keyword searching on encrypted data. First, this scheme specifies a new data protection method
(CP-ABE) is a promising technique to solve this issue, but it also faces several challenges, such as the inefficiency of decrypt able files search, attributes verification and decryption. In this paper, we propose a multiuser searchable encryption scheme with efficient access control for cloud storage, where the keyword
database to the cloud server. In this context, privacy is a primary challenge and it is necessary to fulfill main privacy requirements of database owners and clients. This paper presents protocols for executing keyword search and aggregate SQL queries that preserve the privacy of both the client and the database owner. Client
will be uploaded infrequently. We propose a secure query execution model for such an environment. Our approach is to represent all schemes of each tuple in a plaintext table as one Bloom filter index, and to replace queries with keyword searches of the Bloom filter index. Same values in each tuple are transformed into
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