Abstract
Previous computer protection analysis focuses on current data sets that do not have an update and need one-time releases. Serial data publishing on a complex data collection has only a little bit of literature, although it is not completely considered either. They cannot be used against various backgrounds or the usefulness of the publication of serial data is weak. A new generalization hypothesis is developed on the basis of a theoretical analysis, which effectively decreases the risk of re-publication of certain sensitive attributes. The results suggest that our higher anonymity and lower hiding rates were present in our algorithm. Design and Implementation of new proposed privacy preserving technique: In this phase proposed technique is implemented for demonstrating the entire scenario of data aggregation and their privacy preserving data mining. Comparative Production between the proposed technology and the traditional technology for the application of C.45: In this stage, the performance is evaluated and a comparative comparison with the standard algorithm for the proposed data mining security model is presented
Highlights
Among the privacy issues of cloud [1]We differentiate amongst the following: The deceptive conduct of the cloud provider: The cloud server may be malicious or interested and may inappropriately interpret, use or remove user data
Frequency Analysis Attack[2], repeated User Problems Evaluation, and Surface Analysis Attacks can be seen as significant obstacles that could jeopardize the privacy of outsourced info cloud providers
Et al[1] This paper proposes a new Privacy and Safety Mining Framework focused on Data Mining and Privacy Protection
Summary
Among the privacy issues of cloud [1]We differentiate amongst the following: The deceptive conduct of the cloud provider: The cloud server may be malicious or interested and may inappropriately interpret, use or remove user data. Frequency Analysis Attack[2], repeated User Problems Evaluation, and Surface Analysis Attacks can be seen as significant obstacles that could jeopardize the privacy of outsourced info cloud providers. Later in this survey, several implementations block the server from learning the results of the user. Lack of consumer control: there is little connectivity, control and processing of cloud usage data and applications. The underlying cloud infrastructure is often not controlled or governed, but rather selective oversight and control of the use of management interfaces by the service provider. The expertise of customer care depends on a service model.[3]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Turkish Journal of Computer and Mathematics Education (TURCOMAT)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
