Efficient Execution of Aggregation Queries over Encrypted Relational Databases

Hacıgümüş, Hakan; Iyer, Balakrishna R.; Mehrotra, Sharad

doi:10.1007/978-3-540-24571-1_10

Cited by 135 publications

(90 citation statements)

References 3 publications

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“…Moreover, this makes that much of a query operation over encrypted data can be processed at the database service provider, thereby, improving query performance. Later, in [14], the authors proposed to use the homomorphism encryption techniques to enhance their approach, so as to support aggregation queries over encrypted data, and in [15], the authors further discussed an optimization technique for their approach, i.e., how to use multiple communications between the server and the client to decrease the workload of the client. In order to better support range queries over encrypted data, Hore et al [7] explored an optimal approach to partitioning data domain, thereby, improving the precision of range queries.…”

Section: Related Workmentioning

confidence: 99%

“…By analyzing the traditional order-preserving encryption approach to numerical data, a fuzzy matching encryption approach aiming at character strings was proposed in [19]. 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.…”

Section: Related Workmentioning

confidence: 99%

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

et al. 2017

World Wide Web

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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.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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

“…With the help of an homomorphic function, this approach is extended to support aggregation queries over ciphertexts [34]. The homomorphic encryption function is based on the Privacy Homomorphism (PH) scheme [57], which relies on the difficulty of factoring large composite integers, just like the famous RivestShamir-Adleman (RSA) public-key cryptosystem.…”

Section: Bucketization-based Indexingmentioning

confidence: 99%

Enforcing Privacy in Cloud Databases

Moghadam

Darmont

Gavin

2017

Big Data Analytics and Knowledge Discovery

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Abstract. Outsourcing databases, i.e., resorting to Database-as-a-Service (DBaaS), is nowadays a popular choice due to the elasticity, availability, scalability and pay-as-you-go features of cloud computing. However, most data are sensitive to some extent, and data privacy remains one of the top concerns to DBaaS users, for obvious legal and competitive reasons. In this paper, we survey the mechanisms that aim at making databases secure in a cloud environment, and discuss current pitfalls and related research challenges.

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“…As an example, order preserving encryption has been proposed as an effective solution for supporting range conditions, as well as grouping and ordering clauses (e.g., [1,46]). Aggregate functions can instead be computed if the index over the attribute of interest has been defined through homomorphic encryption techniques, which support the evaluation of arithmetic operators on encrypted data (e.g., [24,30]). Different techniques, which do not fit into the classification above, have also been proposed to the aim of enjoying the advantages of traditional database indexing techniques also in the outsourcing scenario (e.g., in [9] the authors propose to use encrypted B+-trees for the efficient evaluation of range queries).…”

Section: Efficient Access To Encrypted Datamentioning

confidence: 99%

Selective and Private Access to Outsourced Data Centers

Vimercati

Foresti

Livraga

et al. 2015

Handbook on Data Centers

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The advancements in the Information Technology and the rapid diffusion of novel computing paradigms have accelerated the trend of moving data to the cloud. Public and private organizations are more often outsourcing their data centers to the cloud for economic and/or performance reasons, thus making data confidentiality an essential requirement. A basic technique for protecting data confidentiality relies on encryption: data are encrypted by the owner before their outsourcing. Encryption however complicates both the query evaluation and enforcement of access restrictions to outsourced data. In this chapter, we provide an overview of the issues and techniques related to the support of selective and private access to outsourced data in a scenario where the cloud provider is trusted for managing the data but not for reading their content. We therefore illustrate methods for enforcing access control and for efficiently and privately executing queries (at the server side) over encrypted data. We also show how the combined adoption of approaches supporting access control and for efficient query evaluation may cause novel privacy issues that need to be carefully handled.

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Efficient Execution of Aggregation Queries over Encrypted Relational Databases

Cited by 135 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

Enforcing Privacy in Cloud Databases

Selective and Private Access to Outsourced Data Centers

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