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2016 | 45 | 2 | 126-136
Article title

Survey of Secure Two Parties Confidential Information Release in Vertical Partitioned Data

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EN
Abstracts
EN
To securely give person-exact fragile data from two data providers, whereby the mutual data maintains the necessary information for behind data mining tasks. Secured information distributed locations the problem of discovery delicate information when mining for useful data. In this paper, we address the problem of private data publishing, where personal uniqueness for the similar arrangement of people is detained by two parties. Differential privacy is a detailed security show that makes no doubt around an adversary's experience background knowledge. A differentially-private module ensures that the probability of any output (discharged information) is immediately as likely from all about the same information sets and therefore ensures that all outputs are merciless to any singular's data. As it were, a singular's privacy is not at risk in light of the interest in the data set. Specifically, we show a control for differentially private data discharge for vertically-distributed data between two parties in the semi-genuine adversary model. We first present a two-party convention for the exponential mechanism .This convention can be used as a sub convention by some other computation that requires the exponential component in a distributed setting. Likewise, we propose a two-party algorithm that discharges Differentially-private information in a secure way as per the significance of secure multiparty computation.
Publisher

Year
Volume
45
Issue
2
Pages
126-136
Physical description
Contributors
  • Department of CSE, Anna University Regional Campus Coimbatore, Tamil Nadu, India, vijimecse4@gmail.com
author
References
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  • [16] Mohammed N., Alhadidi D., Fung B C M (2014), ‘Secure Two-Party Differentially Private Data Release for Vertically Partitioned Data’, Proc. IEEE Transaction On Dependable And Secure Computing Vol. 11, No.1, pp. 59-70.
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  • [18] Mohammed N., Fung B C M., and Debbabi M (2011), ‘Anonymity Meets Game Theory: Secure Data Integration with Malicious Participants’, Very Large Data Bases J., Vol. 20, No. 4, pp. 567-588.
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Document Type
article
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Identifiers
YADDA identifier
bwmeta1.element.psjd-87d94a70-78e8-4f2f-ba16-066517895a15
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