Fast Query Over Encrypted Character Data in Database

Wang, Zheng-Fei; Dai, Jing; Wang, Wei; Shi, Bao‐Sen

doi:10.1007/978-3-540-30497-5_158

Cited by 25 publications

(22 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Actually, aiming at the problem of querying encrypted textual data in a database, there are some related studies. Wang et al [31] proposed to turn a character string into characteristic values, so as to support similarity queries. This approach can reduce the scope of data decryption, and thus improve query performance.…”

Section: Related Workmentioning

confidence: 99%

“…In this approach, a character string is first transformed to numerical values, and an order-preserving encryption technique in [14] for numerical data, is then used to encrypt the transformed numerical values. To solve the problem of not supporting range queries for the approach in [31], Wu et al [33] defined a structure called n-phase reachability matrix for a character string and used it as the characteristic index values, and then presented split a database query into its server-side representation and client-side representation for partitioning the computation of a query across the client and the server and thus improving query performance. However, it is space-consuming to store a complete reachability matrix.…”

Section: Related Workmentioning

confidence: 99%

“…In this subsection, we compare our approach with three existing ones proposed in [19], [31], and [33], respectively. It should be pointed out that all the approaches were not designed for a CloudDB.…”

Section: Effectiveness Comparison and Analysismentioning

confidence: 99%

“…First, we make an effectiveness comparison in terms of efficiency (i.e., Definition 4). In the experiments, (1) for our approach, the security factor ρ is set to 2 15 ; (2) for the approach in [31], the number of bits of characteristic index field is set to 32 (that is recommended by the authors); and (3) for the approach in [33], the size of an index matrix is set to 8 (for the private field "phone") or 20 (for the private field "name"). The experiments were performed based on the basic similarity queries "PL2" and "NL2", and the basic range queries "PR2" and "NR2".…”

Section: Effectiveness Comparison and Analysismentioning

confidence: 99%

“…The experimental results are shown in Figure 6, where "AP-1", "AP-2" and "AP-3" denotes the approaches presented in [19], [31], and [33], respectively, and "AP-We" denotes our approach. From Figure 6, we see that, our approach has nearly the same running efficiency to the approaches presented in [19] and [31], and has better running efficiency than that presented in [33]. Table 5: The effectiveness comparison, where "low" denotes non-support, "high" denotes good support, and "medium" denote some support…”

Section: Effectiveness Comparison and Analysismentioning

confidence: 99%

See 4 more Smart Citations

An effective approach for the protection of privacy text data in the CloudDB

et al. 2017

World Wide Web

View full text Add to dashboard Cite

Due to the advantages of pay-on-demand, expand-on-demand and high availability, cloud databases (CloudDB) have been widely used in information systems. However, since a CloudDB is distributed on an untrusted cloud side, it is an important problem how to effectively protect massive private information in the CloudDB. Although traditional security strategies (such as identity authentication and access control) can prevent illegal users from accessing unauthorized data, they cannot prevent internal users at the cloud side from accessing and exposing personal privacy information. In this paper, we propose a client-based approach to protect personal privacy in a CloudDB. In the approach, privacy data before being stored into the cloud side, would be encrypted using a traditional encryption algorithm, so as to ensure the security of privacy data. To execute various kinds of query operations over the encrypted data efficiently, the encrypted data would be also augmented with additional feature index, so that as much of each query operation as possible can be processed on the cloud side without the need to decrypt the data. To this end, we explore how the feature index of privacy data is constructed, and how a query operation over privacy data is transformed into a new query operation over the index data so that it can be executed on the cloud side correctly. The effectiveness of the approach is demonstrated by theoretical analysis and experimental evaluation. The results show that the approach has good performance in terms of security, usability and efficiency, thus effective to protect personal privacy in the CloudDB.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Effectiveness Comparison and Analysismentioning

confidence: 99%

Section: Effectiveness Comparison and Analysismentioning

confidence: 99%

Section: Effectiveness Comparison and Analysismentioning

confidence: 99%

See 3 more Smart Citations

An effective approach for the protection of privacy text data in the CloudDB

et al. 2017

World Wide Web

View full text Add to dashboard Cite

show abstract

Preserving Privacy in Data Outsourcing

Foresti

2011

Advances in Information Security

View full text Add to dashboard Cite

The increasing availability of large collections of personal information as well as of data storage facilities for supporting data-intensive services, support the view that service providers will be more and more requested to be responsible for the storage and the efficient and reliable dissemination of information, thus realizing a "data outsourcing" architecture. Within a data outsourcing architecture data are stored together with application front-ends at the sites of an external server who takes full charges of their management. While publishing data on external servers may increase service availability, reducing data owners' burden of managing data, data outsourcing introduces new privacy and security concerns since the server storing the data may be honest-but-curious. A honest-but-curious server honestly manages the data but may not be trusted by the data owner to read their content. To ensure adequate privacy protection, a traditional solution consists in encrypting the outsourced data, thus preventing outside attacks as well as infiltration from the server itself. Such traditional solutions have however the disadvantage of reducing query execution efficiency and of preventing selective information release. This introduces then the need to develop new models and methods for the definition and enforcement of access control and privacy restrictions on outsourced data while ensuring an efficient query execution.In this thesis, we present a comprehensive approach for protecting sensitive information when it is stored on systems that are not under the data owner's control. There are mainly three security requirements that need to be considered when designing a system for ensuring confidentiality of data stored and managed by a honest-but-curious server. The first requirement is access control enforcement to limit the ability of authorized users to access system's resources. In traditional contexts, a trusted module of the data management system is in charge of enforcing the access control policy. In the considered scenario, the service provider is not trusted for enforcing the access control policy and the data owner is not willing to mediate access requests to filter query results. We therefore propose a new access control system, based on selective encryption, that does not require the presence of a trusted module in the system for the enforcement of the policy. The second requirement is privacy protection to limit the visibility of stored/published data to non authorized II users while minimizing the adoption of encryption. Data collections often contain personally identifiable information that needs to be protected both at storage and when disseminated to other parties. As an example, medical data cannot be stored or published along with the identity of the patients they refer to. To guarantee privacy protection and to limit the use of encryption, in this thesis we first propose a solution for modeling in a simple while powerful way privacy requirements through confidentiality constraints, which a...

show abstract

Secure Storage and Fuzzy Query over Encrypted Databases

Liu

et al. 2013

Network and System Security

View full text Add to dashboard Cite

Fast Query Over Encrypted Character Data in Database

Cited by 25 publications

References 3 publications

An effective approach for the protection of privacy text data in the CloudDB

An effective approach for the protection of privacy text data in the CloudDB

Preserving Privacy in Data Outsourcing

Secure Storage and Fuzzy Query over Encrypted Databases

Contact Info

Product

Resources

About