An effective private data storage and retrieval system using secret sharing scheme based on secure multi-party computation
Open accessAbstract
Privacy of the outsourced data is one of the major challenge. Insecurity of the network environment and untrust-worthiness of the service providers are obstacles of making the database as a service. Privacy concerns exist wherever personally identifiable information is collected and stored. Public databases and resources are potential source of risk to user privacy. An intentional database owner can guess user details by practically monitoring their queries. Hence the major challenge here is to share the data by protecting personal information. A data retrieval scheme allowing the users to query the database with out comprpmising the privacy in data item is generally sought The naive solution for confidentiality is to encrypt data before outsourcing. Query execution, key management and statistical inference are major challenges in this case. The proposed system suggests a mechanism to store private information and secure retrieval of this data using secret sharing based Secure Multiparty Computation(SMC). The idea is to develop a mechanism to store private information with a highly available storage provider which could be accessed from anywhere using queries while hiding the actual data values from the storage provider. Multiparty Computation facilitates application of join functions over their private inputs and SMC performs these functions by keeping the input data private. This is achieved by making secret shares of the inputs and manipulating the shares to compute some functions.
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Nair et al. propose a secure information storage and retrieval model based on SMC.
“Nair et al. [116] propose a secure information storage and retrieval model based on SMC.”
From A Survey of Self-Sovereign Identity Ecosystem (2021) · cites this paper as [116]
This model splits sensitive data among multiple databases and reconstructs the data by a computation agent on the client side.
“This model splits sensitive data among multiple databases and reconstructs the data by a computation agent on the client side.”
From A Survey of Self-Sovereign Identity Ecosystem (2021) · cites this paper as [116]
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Cites
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Flagged first, then by citations
Research works printed but not linked: 2
- [2][2] VP Binu and A Sreekumar. An epitome of multi secret sharing schemes for general access structure. arXiv preprint arXiv:1406.5596 , 2014. - · arXiv
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Cited by
Sorted by citations
A Survey of Self-Sovereign Identity Ecosystem
Soltani, R., Nguyen, U. T., & An, A. (2021) · Security and Communication Networks · doi:10.1155/2021/8873429 · Cited by 131 · see citing works
“[116] propose a secure information storage and retrieval model based on SMC.”
MethodPractical Key Recovery Model for Self-Sovereign Identity Based Digital Wallets
Soltani, R., Nguyen, U. T., & An, A. (2019) · 2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) · doi:10.1109/dasc/picom/cbdcom/cyberscitech.2019.00066 · Cited by 39 · see citing works
Decentralized and Privacy-Preserving Key Management Model
Soltani, R., Nguyen, U. T., & An, A. (2020) · 2020 International Symposium on Networks, Computers and Communications (ISNCC) · doi:10.1109/isncc49221.2020.9297294 · Cited by 8 · see citing works
- Authors
- Nair, D. G., Binu, V. P., & Kumar, G. S.
- Affiliations
- Cochin University of Science and Technology (IN)
- Venue
- 2014 International Conference on Data Science & Engineering (ICDSE)
- Publisher
- IEEE
- Published
- 2014-08
- Pages
- 210-214
- OpenAlex
- W2094551710
- Cited by
- 11
- References
- 16
- Citations by year
- 2021: 2 · 2020: 2 · 2019: 2 · 2017: 1 · 2016: 4
- FWCI
- 0.98
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- International Conference on Data Science and Engineering (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- secure data retrieval, secret sharing, secure multi-party computation, outsourced databases, database privacy, personal data protection, query privacy, data confidentiality, key management
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