Privacy Preserving Utility Verification and Security of Data Published by Non-Interactive Differentially Private Mechanisms
Gouri Namdeo Kale1, S. N. Kini2
1Gouri Namdeo Kale, Department of Computer Engineering, Jayawantrao Sawant College of Engineering, Hadapsar Pune-28, Savitribai Phule Pune University, Pune (Maharashtra) India.
2Dr. S. N. Kini, Professor, Department of Computer Engineering, Jayawantrao Sawant College of Engineering, Hadapsar Pune-28, Savitribai Phule Pune University, Pune (Maharashtra) India
Manuscript received on July 17, 2017. | Revised Manuscript Received on July 19, 2017. | Manuscript published on July 25, 2017. | PP: 1-3 | Volume-4 Issue-12, July 2017. | Retrieval Number: L11970741217/2017©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Service providers have the skill to collect large amounts of user data. Sometimes, a set of providers may attempt to combine their data for particular data mining tasks. In this process, how to keep users’ privacy is very critical. Many Users write an own novel, personal story and private dataset, each user need to preserve this data harmless on own site and with user internet amounts of user data. Sometimes, a set of providers may attempt to combine their data for particular data mining tasks. In this process, how to keep users’ privacy is very critical. Many Users write an own novel, personal story and private dataset, each user need to preserve this data harmless on own site and with user internet facility user always search a digital publisher. This is the so-called privacy-preserving collaborative data publishing problem. In this paper, we deliberate the collaborative data publishing problem for anonymizing horizontally partitioned data at several data providers. Meanwhile most anonymization methods have bad impact on data utility. However, this task is non-trivial for the reason the utility measuring usually requires the aggregated raw data, which is not exposed to the data users due to privacy concerns. The paper addresses this new threat, and makes several contributions.
Keywords: Data Privacy, Data security. double level Encryption, Utility verification