ABSTRACT
Using
cloud computing, individuals can store their data on remote servers and allow
data access to public users through the cloud servers. As the outsourced data
are likely to contain sensitive privacy information, they are typically
encrypted before uploaded to the cloud. This, however, significantly limits the
usability of outsourced data due to the difficulty of searching over the encrypted
data. In this paper, we address this issue by developing the fine-grained
multi-keyword search schemes over encrypted cloud data. Our original
contributions are three-fold. First, we introduce the relevance scores and
preference factors upon keywords which enable the precise keyword search and
personalized user experience. Second, we develop a practical and very efficient
multi-keyword search scheme. The proposed scheme can support complicated logic
search the mixed “AND”, “OR” and “NO” operations of keywords. Third, we further
employ the classified sub-dictionaries technique to achieve better efficiency
on index building, trapdoor generating and query. Lastly, we analyze the
security of the proposed schemes in terms of confidentiality of documents, privacy
protection of index and trapdoor, and unlink ability of trapdoor. Through
extensive experiments using the real-world dataset, we validate the performance
of the proposed schemes. Both the security analysis and experimental results
demonstrate that the proposed schemes can achieve the same security level
comparing to the existing ones and better performance in terms of
functionality, query complexity and efficiency.
AIM
The main aim of this paper can
achieve the security level and better
performance in terms of functionality, query complexity and efficiency.
SCOPE
The scope of this paper is to secure
kNN computation scheme to achieve the searchable encryption property.
EXISTING
SYSTEM
Although
many search functionalities have been developed in previous literature towards
precise and efficient searchable encryption, it is still difficult for
searchable encryption to achieve the same user experience as that of the
plaintext search, like Google search. This mainly attributes to following two
issues. Firstly, query with user preferences is very popular in the plaintext
search. It enables personalized search and can more accurately represent user’s
requirements, but has not been thoroughly studied and supported in the
encrypted data domain. Secondly, to further improve the user’s experience on
searching, an important and fundamental function is to enable the multi-keyword
search with the comprehensive logic operations, i.e., the “AND”, “OR” and “NO”
operations of keywords. This is fundamental for search users to prune the
searching space and quickly identify the desired data.
DISADVANTAGES:
- The Computation Overhead is greatly affected by the size of dictionary and the number of documents, and almost has no relation to the number of query keywords
- It significantly limits the usability of outsourced data due to the difficulty of searching over the encrypted data.
PROPOSED SYSTEM
To
propose a variant of the secure kNN computation scheme and it serves as the
basic framework of our schemes. The secure kNN computation scheme uses
Euclidean distance to select k nearest database records. In this section, we
present a variant of the secure kNN computation scheme to achieve the
searchable encryption property.
ADVANTAGES:
- To significantly reduce the computation and communication overhead.
- It can achieve confidentiality of documents, privacy protection of index and trapdoor, and unlink ability of trapdoor
SYSTEM ARCHITECTURE:-
SYSTEM CONFIGURATION
HARDWARE REQUIREMENTS:
Processor - Pentium –III
- Speed - 1.1 Ghz
- RAM - 256 MB(min)
- Hard Disk - 20 GB
- Floppy Drive - 1.44 MB
- Key Board - Standard Windows Keyboard
- Mouse - Two or Three Button Mouse
- Monitor - SVGA
SOFTWARE REQUIREMENTS:-
- Operating System : Windows 7
- Front End : JSP AND SERVLET
- Database : MYSQL
REFERENCES
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