Techniques which are already existing are not
having the high clustering to the encrypted data on cloud,
therefore, to solve the classification problem on encrypted
data. A k-NN algorithm for classification of encrypted data
in the cloud, is also proposed for security purpose. In this
paper we proposed the the new DBSCAN algorithm which
will provide the better clustering than the K-NN clustering of
the data on the cloud, provides In day by day the popularity
of web services are attracting with their rapid development,
As a result, there is a huge amount of heterogeneous data.
The data needs to be mine for various applications in many
organizations like scientific research, medicine and among
government agencies. Data Mining is perspective is on a very
large scale. Classification of outsourced data is One of the
most important tasks in data mining applications. So in data
mining area many practical as well as theoretical solutions to
the classification problem have been proposed. As as a
privacy issues solution, Different security models used in
different solutions. The recent needs of IT make Cloud
Computing to exist. Always users can outsource encrypted
form of their data in and the data mining tasks to the cloud.
Privacy preserving classification security to user’s input
query and hiding the data accessing patterns on the cloud. As
well as it will provide better clustering solution for the
outsourced data.
Published In:IJCSN Journal Volume 5, Issue 4
Date of Publication : August 2016
Pages : 594-598
Figures :--
Tables : --
Chaitali Shewale : Computer Department, ZCOER
SPI Pune University
Pune, India
S.M. Sangve : Computer Department, ZCOER
SPI Pune University
Pune, India
This paper presents various existing methods from
different papers used for the privacy preserving query
processing in data mining and over encrypted data can
mention as (PPDM). To protect user data privacy, with
the discussion of various proposals of privacy-preserving
classification techniques are presented over the past
papers. The existing techniques are applicable to
outsourced database environments where the data resides
in encrypted form on a third-party server and also the
classification or clustering of the data with proper label is
discussed here This paper proposed a new privacypreserving
clustering protocol DBSCAN is used over
encrypted data of the cloud. This protocol protects the
confidentiality of the data, as a user’s input query, and
hides the data access patterns. As well as provide fast
access to data as better clustering is done using DBSCAN
algorithm.
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