Enabling Fine-Grained Multi-Keyword Search Supporting Classified Sub-Dictionaries Over Encrypted Cloud Data

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:

1.  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
2.  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:

1. To significantly reduce the computation and communication overhead.
2. It can achieve confidentiality of documents, privacy protection of index and trapdoor, and unlink ability of trapdoor

SYSTEM ARCHITECTURE:-

SYSTEM CONFIGURATION:-

Hardware Requirements

• Speed                  -    1.1 Ghz
• Processor              -    Pentium IV
• RAM                    -    512 MB (min)
• Hard Disk            -    40 GB
• Key Board                    -    Standard Windows Keyboard
• Mouse                  -    Two or Three Button Mouse
• Monitor                -     LCD/LED

 Software requirements

• Operating System              : Windows 7             
•  Front End                           : ASP.Net and C#
• Database                             : MSSQL
• Tool                                    : Microsoft Visual studio

REFERENCES

Li, H. Yang, Y.  Luan, T.  Liang, X.,“ ENABLING FINE-GRAINED MULTI-KEYWORD SEARCH SUPPORTING CLASSIFIED SUB-DICTIONARIES OVER ENCRYPTED CLOUD DATA,” IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING,VOL PP,ISS 99, FEBRUARY 2015.