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Privacy-Preserving Multi-
keyword Ranked Search
over Encrypted Cloud DataPrivacy-Preserving Multi-keyword Ranked Search
over Encrypted Cloud Data
Ning Cao†, Cong Wang‡, Ming Li†, Kui Ren‡, and Wenjing Lou†
†Department of ECE, Worcester Polytechnic Institute, Email: {ncao, mingli, wjlou}@ece.wpi.edu,
‡Department of ECE, Illinois Institute of Technology, Email: {cong, kren}@ece.iit.edu
Abstract
With the advent of cloud computing, data owners are motivated to outsource their complex data
management systems from local sites to the commercial public cloud for great flexibility and
economic savings. But for protecting data privacy, sensitive data has to be encrypted before
outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus,
enabling an encrypted cloud data search service is of paramount importance. Considering the large
number of data users and documents in the cloud, it is necessary to allow multiple keywords in the
search request and return documents in the order of their relevance to these keywords. Related
works on searchable encryption focus on single keyword search or Boolean keyword search, and
rarely sort the search results. In this paper, for the first time, we define and solve the challenging
problem of privacy preserving multi-keyword ranked search over encrypted cloud data (MRSE).We
establish a set of strict privacy requirements for such a secure cloud data utilization system. Among
various multi keyword semantics, we choose the efficient similarity measure of “coordinate
matching”, i.e., as many matches as possible, to capture the relevance of data documents to the
search query. We further use “inner product similarity” to quantitatively evaluate such similarity
measure. We first propose a basic idea for the MRSE based on secure inner product computation,
and then give two significantly improved MRSE schemes to achieve various stringent privacy
requirements in two different threat models. Thorough analysis investigating privacy and efficiency
guarantees of proposed schemes is given. Experiments on the real-world dataset further show
proposed schemes indeed introduce low overhead on computation and communication.
Existing System
The large number of data users and documents in cloud, it is crucial for the
search service to allow multi-keyword query and provide result similarity ranking
to meet the effective data retrieval need. The searchable encryption focuses on
single keyword search or Boolean keyword search, and rarely differentiates the
search results.
Disadvantages of Existing System
 Single-keyword search without ranking
 Boolean- keyword search without ranking
 Single-keyword search with ranking
Proposed System
We define and solve the challenging problem of privacy-preserving multi-keyword
ranked search over encrypted cloud data (MRSE), and establish a set of strict
privacy requirements for such a secure cloud data utilization system to become a
reality. Among various multi-keyword semantics, we choose the efficient
principle of “coordinate matching”.
Advantages of Proposed System
 Multi-keyword ranked search over encrypted cloud data (MRSE)
Architecture
Modules
 Data User Module
 Data Owner Module
 File Upload Module
 Encryption
 Rank Search Module
 File Download Module
 Decryption
 View Uploaded and Downloaded File
Modules Description
 Data User Module: This module include the user registration login details.
 Data Owner Module: This module helps the owner to register them details
and also include login details.
 File Upload Module: This module help the owner to upload his file with
encryption using RSA algorithm. This ensure the files to be protected from
unauthorized user.
 Rank Search Module: This module ensure the user to search the file that are searched
frequently using rank search.
 File Download Module: This module allows the user to download the file using his secret key to
decrypt the downloaded data.
 View Uploaded and Downloaded File: This module allows the Owner to view the uploaded files
and downloaded files
Minimum Hardware Configuration of the
Proposed System
 Processor : Intel/AMD
 Hard Disk : 40 GB
 Monitor : 14’ Colour Monitor
 Mouse : Optical Mouse
 RAM : 512 MB
Software Configuration of the
Proposed System
 Operating system : Windows 7 and above
 Coding Language : ASP.Net with C#
 Data Base : SQL Server 2008
References
 L. M. Vaquero, L. Rodero-Merino, J. Caceres, and M. Lindner, “A break in the
clouds: towards a cloud definition,” ACM SIGCOMM Comput. Commun. Rev.,
vol. 39, no. 1, pp. 50–55, 2009.
 S. Kamara and K. Lauter, “Cryptographic cloud storage,” in RLCPS, January
2010, LNCS. Springer, Heidelberg.
 A. Singhal, “Modern information retrieval: A brief overview,” IEEE Data
Engineering Bulletin, vol. 24, no. 4, pp. 35–43, 2001.
 I. H. Witten, A. Moffat, and T. C. Bell, “Managing gigabytes: Compressing and
indexing documents and images,” Morgan Kaufmann Publishing, San
Francisco, May 1999.
 D. Song, D. Wagner, and A. Perrig, “Practical techniques for searches on
encrypted data,” in Proc. of S&P, 2000.

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Privacy preserving multi-keyword ranked search over encrypted cloud data

  • 1. Privacy-Preserving Multi- keyword Ranked Search over Encrypted Cloud DataPrivacy-Preserving Multi-keyword Ranked Search over Encrypted Cloud Data Ning Cao†, Cong Wang‡, Ming Li†, Kui Ren‡, and Wenjing Lou† †Department of ECE, Worcester Polytechnic Institute, Email: {ncao, mingli, wjlou}@ece.wpi.edu, ‡Department of ECE, Illinois Institute of Technology, Email: {cong, kren}@ece.iit.edu
  • 2. Abstract With the advent of cloud computing, data owners are motivated to outsource their complex data management systems from local sites to the commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data has to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in the cloud, it is necessary to allow multiple keywords in the search request and return documents in the order of their relevance to these keywords. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely sort the search results. In this paper, for the first time, we define and solve the challenging problem of privacy preserving multi-keyword ranked search over encrypted cloud data (MRSE).We establish a set of strict privacy requirements for such a secure cloud data utilization system. Among various multi keyword semantics, we choose the efficient similarity measure of “coordinate matching”, i.e., as many matches as possible, to capture the relevance of data documents to the search query. We further use “inner product similarity” to quantitatively evaluate such similarity measure. We first propose a basic idea for the MRSE based on secure inner product computation, and then give two significantly improved MRSE schemes to achieve various stringent privacy requirements in two different threat models. Thorough analysis investigating privacy and efficiency guarantees of proposed schemes is given. Experiments on the real-world dataset further show proposed schemes indeed introduce low overhead on computation and communication.
  • 3. Existing System The large number of data users and documents in cloud, it is crucial for the search service to allow multi-keyword query and provide result similarity ranking to meet the effective data retrieval need. The searchable encryption focuses on single keyword search or Boolean keyword search, and rarely differentiates the search results.
  • 4. Disadvantages of Existing System  Single-keyword search without ranking  Boolean- keyword search without ranking  Single-keyword search with ranking
  • 5. Proposed System We define and solve the challenging problem of privacy-preserving multi-keyword ranked search over encrypted cloud data (MRSE), and establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality. Among various multi-keyword semantics, we choose the efficient principle of “coordinate matching”.
  • 6. Advantages of Proposed System  Multi-keyword ranked search over encrypted cloud data (MRSE)
  • 8. Modules  Data User Module  Data Owner Module  File Upload Module  Encryption  Rank Search Module  File Download Module  Decryption  View Uploaded and Downloaded File
  • 9. Modules Description  Data User Module: This module include the user registration login details.  Data Owner Module: This module helps the owner to register them details and also include login details.  File Upload Module: This module help the owner to upload his file with encryption using RSA algorithm. This ensure the files to be protected from unauthorized user.
  • 10.  Rank Search Module: This module ensure the user to search the file that are searched frequently using rank search.  File Download Module: This module allows the user to download the file using his secret key to decrypt the downloaded data.  View Uploaded and Downloaded File: This module allows the Owner to view the uploaded files and downloaded files
  • 11. Minimum Hardware Configuration of the Proposed System  Processor : Intel/AMD  Hard Disk : 40 GB  Monitor : 14’ Colour Monitor  Mouse : Optical Mouse  RAM : 512 MB
  • 12. Software Configuration of the Proposed System  Operating system : Windows 7 and above  Coding Language : ASP.Net with C#  Data Base : SQL Server 2008
  • 13. References  L. M. Vaquero, L. Rodero-Merino, J. Caceres, and M. Lindner, “A break in the clouds: towards a cloud definition,” ACM SIGCOMM Comput. Commun. Rev., vol. 39, no. 1, pp. 50–55, 2009.  S. Kamara and K. Lauter, “Cryptographic cloud storage,” in RLCPS, January 2010, LNCS. Springer, Heidelberg.  A. Singhal, “Modern information retrieval: A brief overview,” IEEE Data Engineering Bulletin, vol. 24, no. 4, pp. 35–43, 2001.  I. H. Witten, A. Moffat, and T. C. Bell, “Managing gigabytes: Compressing and indexing documents and images,” Morgan Kaufmann Publishing, San Francisco, May 1999.  D. Song, D. Wagner, and A. Perrig, “Practical techniques for searches on encrypted data,” in Proc. of S&P, 2000.