Symmetrically-Private Database Search in Cloud Computing

Barouti, Samira; Alhadidi, Dima; Debbabi, Mourad

doi:10.1109/cloudcom.2013.95

Cited by 7 publications

(8 citation statements)

References 14 publications

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“…In this section, we present a quick overview of the protocol proposed by Barouti et al [2] to protect database confidentiality and enable a client to execute SQL queries over the encrypted database without decryption. The proposed protocol handles aggregate queries over encrypted databases stored on the cloud.…”

Section: Secure Data Managementmentioning

confidence: 99%

“…Query predicates are evaluated using the GM cryptosystem and Fischlin's protocol whereas query aggregate functions are computed using the Paillier cryptosystem [9]. In the remaining of this section, we describe the basic steps of our protocol (see [2] for details).…”

Section: Secure Data Managementmentioning

confidence: 99%

“…The proxy initiates the search by retrieving the content of the tree root at index 1 of the table T using Private Information Retrieval (PIR) [2]; it then extracts Δ and c from the retrieved item. Decryption of these sequences using the decryption keys enables the proxy to evaluate the query conditions.…”

Section: Secure Data Managementmentioning

confidence: 99%

“…• We adopt a new privacy-enhancing protocol that can provide data confidentiality against an untrusted cloud servers by using semantically-secure encryption schemes. The protocol has been proposed by Barouti et al [2] (Section III). We then extend the protocol to support aggregate queries or complex data mining tasks on encrypted data while preventing inference attacks.…”

Section: Introductionmentioning

confidence: 99%

“…Most of the previous proposals on secure outsourced databases suggest encrypting the data before moving it to the cloud [2]. While encryption can provide data confidentiality, it is of little use in deterring inference attacks [1].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Secure and Private Management of Healthcare Databases for Data Mining

Mohammed

Barouti

Alhadidi

et al. 2015

2015 IEEE 28th International Symposium on Computer-Based Medical Systems

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There has been a tremendous growth in health data collection since the development of Electronic Medical Record (EMR) systems. Such collected data is further shared and analyzed for diverse purposes. Despite many benefits, data collection and sharing have become a big concern as it threatens individual privacy. In this paper, we propose a secure and private data management framework that addresses both the security and privacy issues in the management of medical data in outsourced databases. The proposed framework ensures the security of data by using semantically-secure encryption schemes to keep data encrypted in outsourced databases. The framework also provides a differentially-private query interface that can support a number of SQL queries and complex data mining tasks. We experimentally evaluate the performance of the proposed framework, and the results show that the proposed framework is practical and has low overhead.

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Section: Secure Data Managementmentioning

confidence: 99%

Section: Secure Data Managementmentioning

confidence: 99%

Section: Secure Data Managementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Secure and Private Management of Healthcare Databases for Data Mining

Mohammed

Barouti

Alhadidi

et al. 2015

2015 IEEE 28th International Symposium on Computer-Based Medical Systems

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Interoperability Between SaaS and Data Layers: Enhancing the MIDAS Middleware

Ribeiro

Vieira

Claro

et al. 2019

Communications in Computer and Information Science

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Secure and Privacy-Preserving Querying of Personal Health Records in the Cloud

Barouti

Aljumah

Alhadidi

et al. 2014

Lecture Notes in Computer Science

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International audiencePersonal Health Records (PHR) are user-friendly, online solutions that give patients a way of managing their own health information. Many of the current PHR systems allow storage providers to access patients’ data. Recently, architectures of storing PHRs in cloud have been proposed. However, privacy remains a major issue for patients. Consequently, it is a promising method to encrypt PHRs before outsourcing. Encrypting PHRs prevents health organizations from analyzing medical data. In this paper, we propose a protocol that would allow health organizations to produce statistical information about encrypted PHRs stored in the cloud. The protocol depends on two threshold homomorphic cryptosystems: Goldwasser-Micali (GM) and Paillier. It executes queries on Kd-trees that are constructed from encrypted health records. It also prevents patients from inferring what health organizations are concerned about. We experimentally evaluate the performance of the proposed protocol and report on the results of implementation

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Symmetrically-Private Database Search in Cloud Computing

Cited by 7 publications

References 14 publications

Secure and Private Management of Healthcare Databases for Data Mining

Secure and Private Management of Healthcare Databases for Data Mining

Interoperability Between SaaS and Data Layers: Enhancing the MIDAS Middleware

Secure and Privacy-Preserving Querying of Personal Health Records in the Cloud

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