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International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 
E-ISSN: 2321-9637 
39 
Secure Ranked Keyword Search Over Cloud Data 
MS. M. R. GIRME 1, PROF. G.M. BHANDARI 2 
ME Computer Engg, 1, 2, JSPM’s BSIOTR, Wagholi, Pune-141, 2, 
Email: mayura.shelke@gmail.com1 
Abstract- Now a day’s cloud computing becoming so popular due to attractive features of cloud, users are 
storing large amount of data on cloud storage, these data may be users personal or secret. After storing data user 
can access data any time without any burden of hardware and software. But outsourcing plaintext data is big risk 
in cloud. So to protect data privacy data has to be encrypted before outsourced to the cloud and also to retrieve 
the data files correctly, introducing ranked keyword search mechanisms. So, in this paper implementing ranked 
keyword search over outsourced cloud data. 
Index Terms- IAAS, OPSE, PAAS, RSSE, SAAS etc 
1. INTRODUCTION 
Today the latest paradigm to emerge is that of Cloud 
computing provides reliable services delivered 
through data centers that are built on virtualized 
compute and storage technologies [1][2]. Cloud 
Computing becomes more sensitive information are 
being centralized into the cloud such as e-mails, 
personal health records, company finance data, and 
government documents, etc. The fact that data owners 
and cloud server are no longer in the same trusted 
domain may put the outsourced unencrypted data at 
risk the cloud server may be leak data information to 
unauthorized entities are hacked. Data encryption 
makes effective data utilization is a very challenging 
task. Besides, in Cloud Computing, data owners may 
share their outsourced data with a large number of 
users, who might want to only retrieve certain specific 
data files they are interested in during a given session 
Such keyword search technique allows users to 
selectively retrieve files of interest and has been 
widely applied in plain text search scenarios 
Unfortunately, data encryption, which restricts user’s 
ability to perform keyword search and further 
demands the protection of keyword privacy makes 
the traditional plaintext search methods fail for 
encrypted cloud data. 
2. LITERATURE SURVEY 
We have done a survey on existing searching methods 
Practical Techniques for Searches on encrypted data 
(PTSED) [6], Secure Index (SI)[7] and Public key 
encryption (PKE)[8] and summarized with following 
characteristic [5]. We also compared this study with 
our proposed system. 
I. Sequential approach 
This method will find a particular keyword in a 
document, which will check for every one of its 
elements, and will display the search result one at a 
time and in linear order and this will decrease the 
performance i.e for example Searching ”a[a-z]b” 
,needs 26 queries. 
II. Document Index 
Storing a secure keyword index in cloud. This kind of 
index will allow a query to check if the documents 
contain a keyword and will retrieve the files. It will 
not search for the entire document based on index 
keyword will retrieve the documents that are 
especially useful for large documents and large 
document. 
III. Perform keywords filter 
Indexing of keyword contains unique keywords; it 
will not contain the duplicate keywords in index files. 
IV. Public Key authentication 
This kind of encryption will allow anyone to access 
the data in cloud, which is not efficient one. 
Table 1. System comparative analysis 
Characteristic PTSED SI PKE Proposed 
System 
Sequential 
Approach 
Yes No Yes Not 
supported. 
Document 
Index 
No Yes No Yes 
Keyword 
Filter 
No Yes No Yes 
Secret Key Public No Public Private 
Cloud 
No No Yes Yes 
computing 
The following fig.1 shows the comparative analysis of 
different systems with proposed system. The proposed 
system satisfied most of the characteristics of existing 
system. 
.
International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 
E-ISSN: 2321-9637 
Characteristic 
s Range 
Fig 1. System comparative analysis 
4.5 
4 
3.5 
3 
2.5 
2 
1.5 
1 
0.5 
0 
3. PROPOSED SYSTEM 
We focus on cloud data storage security. To ensure 
the correctness of users’ data in the cloud, we define 
and solve the problem of secure ranked keyword 
search rch over encrypted cloud data. We explore the 
statistical measure approach, i.e. relevance score, 
from information retrieval to build a secure searchable 
index, and develop a one-to-many order-order 
preserving 
mapping technique. The resulting design is able to 
facilitate efficient server-side ranking without losing 
keyword privacy. The new scheme further supports 
secure and efficient dynamic operations on data 
blocks, including: data update, delete and append. 
· Goal and Objectives 
The goal of the project is to enable ranked searchable 
symmetric encryption for effective utilization of 
outsourced and encrypted cloud data under the 
aforementioned model; system design should achieve 
the security and performance guarantee. The 
objectives of the project are as below: 
1. Ranked keyword search 
To explore different mechanisms for designing 
effective ranked search schemes based on the existing 
searchable encryption framework. 
2. Security guarantee 
To prevent cloud server from learning the plain text of 
either the data files or the searched keywords, and 
achieve the as strong-as-possible security strength 
compared to existing searchable encryption schemes. 
3. Efficiency 
Above goals should be achieved with minimum 
communication and computation overhead 
4. SYSTEM ARCHITECTURE 
We consider an encrypted cloud data hosting service 
involving three different entities: data owner, data 
user, er, and cloud server as in fig.2 
Data owner has a 
collection of n data files C= (f1, f2...fn) that he wants 
to outsource on the cloud server so, before 
outsourcing, data owner will first build a secure 
searchable index I from a set of m distinct keywords 
W = (w1,w2…wm) extracted from the file collection C, 
and store both the index I and the encrypted file 
collection C on the cloud server. We assume the 
authorization between the data owner and users is 
appropriately done. To search the file collection for a 
given keyword w, an authorized user generates and 
submits a search request in a secret form 
Tw of the keyword w to the cloud server. Upon 
receiving the search request T 
responsible to search the index I and return the 
corresponding set of files to the user. We consider the 
secure ranked keyword search problem as follows: the 
search result should be returned according to certain 
ranked relevance criteria. 
Fig 2. System architecture [2 
· System Modules 
1. Encrypted File Outsource/Upload module 
In this module owner can upload file to cloud server. 
Whole file data is encrypted by server and stored to 
server. 
2. Keyword Indexing Module 
In this module keyword from document will be 
extracted and index of such keywords along with the 
list of documents which contains keywords. This 
index is also encrypted. Index building is done using 
below algorithm. 
3. User Query module 
In this module User searches documents by using 
keywords. Relevance score of document is calculated 
for searched keywords for documents whose 
keywords are matched. Based on this calculated 
relevance score, and result will be displayed 
according to this relevance score. 
4. Document Retrieval module 
Finally decrypted document is given to user if 
authentication is made between them. Whole process 
don only in encrypted 
5. DESIGN PROCESS 
40 
ing, ) ion form—a trapdoor 
he Tw, the cloud server is 
2] 
arches
International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 
E-ISSN: 2321-9637 
The following fig.3 shows design process of 
Fig 3. Design process 
system. 
1. Mathematical Model Design & 
Algorithms 
· Ranking Function- It is used to calculate 
relevance (frequency) score of keyword. 
Score (Q, Fd) =ΣtεQ 1/|Fd|.(1+ln f 
Parameters 
• Q - searched keywords; 
• fd,t - TF of term t in file Fd; 
• ft - number of files that contain term t; 
• N -The total number of files in the 
collection; 
|.(fd,t) .ln(1+N/ft) 
• |Fd| -Length of file Fd, 
keyword.[9] 
; 
· One-to-many Order Preserving Mapping 
In the searchable index, for each keyword, every 
relevance score will always bind To a specific file ID. 
For e.g. index list for keyword “network” 
“Network” = F1||1; F2||1; F4|||1; …………… 
With file ID as part of seed, for the same plain text, 
the cipher text will be randomly selected within the 
same interval everytime.So following followin 
diagram shows 
overview of OPM[10] plain text to cipher text 
assignment process. Here plaintext ’m’ is first mapped 
to a non-overlapping interval in range, determined by 
encryption key. Ciphertext ’c’ is then chosen by using 
numerical plain text ’m’ as seed. 
Plaintext mapped to random Random chiphertext selection 
Sized Non overlapping interval 
via seed “1|| F4 
Fig 4: OPM algorithm process 
· AES Algorithm 
AES (Advanced Encryption Standard 
symmetric encryption/decryption algorithm 
Follo 
wing 
Fig.5 
shows 
AES 
algorit 
hms 
struct 
ure 
for 
encry 
ption 
and 
decry 
ption. 
Encryption 
Standard) [11] is a 
Fig 5. AES 
1 
2 
. 
. 
M-1 
M 
NN 
algorithm. 
Decryption 
41 
1 
2 
3 
4 
5 
. 
. 
. 
N-2 
N-1 
1 
2 
3 
. 
. 
. 
. 
N-2 
N-1 
N
International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 
E-ISSN: 2321-9637 
42 
6. RESULT 
Fig 6(a). User Registration 
Fig 6(b).User Login 
Fig 6(c) Searched keyword 
Fig 6(e). Upload file 
7. CONCLUSION 
Cloud computing is one of the current most important 
and promising technologies. A data owner can store 
his data in cloud and user could retrieve data files 
whenever needed. To retrieve data files correctly we 
introduce ranked keyword search mechanism. In this
International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 
E-ISSN: 2321-9637 
43 
paper we motivate and solve the problem of 
supporting efficient ranked keyword search for 
achieving effective utilization of remotely stored 
encrypted data in Cloud Computing. Then 
appropriately weaken the security guarantee, resort to 
the newly developed crypto primitive OPSE, and 
derive an efficient one-to-many order-preserving 
mapping function. For future works, a new scheme 
could be developed the authentication of ranked 
search results, and the reversibility of our proposed 
one-to-many order-preserving mapping technique, 
and searching technique for audio and video. 
REFERENCES 
[1] Yanbin Lu and Gene Tsudik,”Enhancing Data 
Privacy in the Cloud”,University of California, 
Irvine 
[2] C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, 
”Secure ranked keyword search over encrypted 
cloud data”,in Proc. of ICDCS’10,2010. 
[3] Kiruthigapriya Sengoden, Swaraj Paul , 
”Improving the Efficiency of Ranked keyword 
Search over Cloud Data”, International Journal of 
Advanced Research in Computer Engineering 
and Technology (IJARCET) Volume 2,Issue 3, 
March 2013. 
[4] Ms Mayura R. Girme, Prof.G.M. Bhandari, 
”Efficient Secure Ranked keyword search 
Algorithms over outsource cloud data”, 
International Journal of Emerging Trends and 
Technology in Computer Science (ISSN 2278- 
6856), Volume 2, Issue 5,September- October 
2013 
[5] Pooja Shah, Gopal Pandey,”Keyword Searching 
techniques for Encrypted Cloud data”, 
Department of Information Technology, Shantilal 
Shah Engineering College,Bhavnagar 
[6] D. Song, D. Wagner, and A. Perrig, ”Practical 
techniques for searches on encrypted data”,in 
Proc. of IEEE Symposium on Security and 
Privacy’00, 2000. 
[7] E.-J. Goh,”Secure indexes”, Cryptology ePrint 
Archive, Report 2003/216. 
[8] D. Boneh, G. D. Crescenzo, R. Ostrovsky, and G. 
Persiano, ”Public key encryption with keyword 
search”,in Proc. of EUROCRYP’04,volume 3027 
of LNCS. Springer,2004. 
[9] Cong Wang, Ning Cao, Kui Ren , Wenjing Lou, 
Senio(2012),”Enabling Secure and Efficient 
Ranked Keyword Search over Outsourced Cloud 
Data”, IEEE Transactions on Parallel and 
Distributed systems, VOL.23,NO.8. 
[10]Alexandra Boldyreva, Nathan Chenette, Younho 
Lee, and Adam O’Neill Georgia,”Order- 
Preserving Symmetric Encryption”,in Proc. of 
Eurocrypt’09, volume 5479 of LNCS. Springer 
2009. 
[11] http://www.facweb.iitkgp.ernet.in/sourav/AES.pdf

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Paper id 28201425

  • 1. International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 E-ISSN: 2321-9637 39 Secure Ranked Keyword Search Over Cloud Data MS. M. R. GIRME 1, PROF. G.M. BHANDARI 2 ME Computer Engg, 1, 2, JSPM’s BSIOTR, Wagholi, Pune-141, 2, Email: mayura.shelke@gmail.com1 Abstract- Now a day’s cloud computing becoming so popular due to attractive features of cloud, users are storing large amount of data on cloud storage, these data may be users personal or secret. After storing data user can access data any time without any burden of hardware and software. But outsourcing plaintext data is big risk in cloud. So to protect data privacy data has to be encrypted before outsourced to the cloud and also to retrieve the data files correctly, introducing ranked keyword search mechanisms. So, in this paper implementing ranked keyword search over outsourced cloud data. Index Terms- IAAS, OPSE, PAAS, RSSE, SAAS etc 1. INTRODUCTION Today the latest paradigm to emerge is that of Cloud computing provides reliable services delivered through data centers that are built on virtualized compute and storage technologies [1][2]. Cloud Computing becomes more sensitive information are being centralized into the cloud such as e-mails, personal health records, company finance data, and government documents, etc. The fact that data owners and cloud server are no longer in the same trusted domain may put the outsourced unencrypted data at risk the cloud server may be leak data information to unauthorized entities are hacked. Data encryption makes effective data utilization is a very challenging task. Besides, in Cloud Computing, data owners may share their outsourced data with a large number of users, who might want to only retrieve certain specific data files they are interested in during a given session Such keyword search technique allows users to selectively retrieve files of interest and has been widely applied in plain text search scenarios Unfortunately, data encryption, which restricts user’s ability to perform keyword search and further demands the protection of keyword privacy makes the traditional plaintext search methods fail for encrypted cloud data. 2. LITERATURE SURVEY We have done a survey on existing searching methods Practical Techniques for Searches on encrypted data (PTSED) [6], Secure Index (SI)[7] and Public key encryption (PKE)[8] and summarized with following characteristic [5]. We also compared this study with our proposed system. I. Sequential approach This method will find a particular keyword in a document, which will check for every one of its elements, and will display the search result one at a time and in linear order and this will decrease the performance i.e for example Searching ”a[a-z]b” ,needs 26 queries. II. Document Index Storing a secure keyword index in cloud. This kind of index will allow a query to check if the documents contain a keyword and will retrieve the files. It will not search for the entire document based on index keyword will retrieve the documents that are especially useful for large documents and large document. III. Perform keywords filter Indexing of keyword contains unique keywords; it will not contain the duplicate keywords in index files. IV. Public Key authentication This kind of encryption will allow anyone to access the data in cloud, which is not efficient one. Table 1. System comparative analysis Characteristic PTSED SI PKE Proposed System Sequential Approach Yes No Yes Not supported. Document Index No Yes No Yes Keyword Filter No Yes No Yes Secret Key Public No Public Private Cloud No No Yes Yes computing The following fig.1 shows the comparative analysis of different systems with proposed system. The proposed system satisfied most of the characteristics of existing system. .
  • 2. International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 E-ISSN: 2321-9637 Characteristic s Range Fig 1. System comparative analysis 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 3. PROPOSED SYSTEM We focus on cloud data storage security. To ensure the correctness of users’ data in the cloud, we define and solve the problem of secure ranked keyword search rch over encrypted cloud data. We explore the statistical measure approach, i.e. relevance score, from information retrieval to build a secure searchable index, and develop a one-to-many order-order preserving mapping technique. The resulting design is able to facilitate efficient server-side ranking without losing keyword privacy. The new scheme further supports secure and efficient dynamic operations on data blocks, including: data update, delete and append. · Goal and Objectives The goal of the project is to enable ranked searchable symmetric encryption for effective utilization of outsourced and encrypted cloud data under the aforementioned model; system design should achieve the security and performance guarantee. The objectives of the project are as below: 1. Ranked keyword search To explore different mechanisms for designing effective ranked search schemes based on the existing searchable encryption framework. 2. Security guarantee To prevent cloud server from learning the plain text of either the data files or the searched keywords, and achieve the as strong-as-possible security strength compared to existing searchable encryption schemes. 3. Efficiency Above goals should be achieved with minimum communication and computation overhead 4. SYSTEM ARCHITECTURE We consider an encrypted cloud data hosting service involving three different entities: data owner, data user, er, and cloud server as in fig.2 Data owner has a collection of n data files C= (f1, f2...fn) that he wants to outsource on the cloud server so, before outsourcing, data owner will first build a secure searchable index I from a set of m distinct keywords W = (w1,w2…wm) extracted from the file collection C, and store both the index I and the encrypted file collection C on the cloud server. We assume the authorization between the data owner and users is appropriately done. To search the file collection for a given keyword w, an authorized user generates and submits a search request in a secret form Tw of the keyword w to the cloud server. Upon receiving the search request T responsible to search the index I and return the corresponding set of files to the user. We consider the secure ranked keyword search problem as follows: the search result should be returned according to certain ranked relevance criteria. Fig 2. System architecture [2 · System Modules 1. Encrypted File Outsource/Upload module In this module owner can upload file to cloud server. Whole file data is encrypted by server and stored to server. 2. Keyword Indexing Module In this module keyword from document will be extracted and index of such keywords along with the list of documents which contains keywords. This index is also encrypted. Index building is done using below algorithm. 3. User Query module In this module User searches documents by using keywords. Relevance score of document is calculated for searched keywords for documents whose keywords are matched. Based on this calculated relevance score, and result will be displayed according to this relevance score. 4. Document Retrieval module Finally decrypted document is given to user if authentication is made between them. Whole process don only in encrypted 5. DESIGN PROCESS 40 ing, ) ion form—a trapdoor he Tw, the cloud server is 2] arches
  • 3. International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 E-ISSN: 2321-9637 The following fig.3 shows design process of Fig 3. Design process system. 1. Mathematical Model Design & Algorithms · Ranking Function- It is used to calculate relevance (frequency) score of keyword. Score (Q, Fd) =ÎŁtεQ 1/|Fd|.(1+ln f Parameters • Q - searched keywords; • fd,t - TF of term t in file Fd; • ft - number of files that contain term t; • N -The total number of files in the collection; |.(fd,t) .ln(1+N/ft) • |Fd| -Length of file Fd, keyword.[9] ; · One-to-many Order Preserving Mapping In the searchable index, for each keyword, every relevance score will always bind To a specific file ID. For e.g. index list for keyword “network” “Network” = F1||1; F2||1; F4|||1; …………… With file ID as part of seed, for the same plain text, the cipher text will be randomly selected within the same interval everytime.So following followin diagram shows overview of OPM[10] plain text to cipher text assignment process. Here plaintext ’m’ is first mapped to a non-overlapping interval in range, determined by encryption key. Ciphertext ’c’ is then chosen by using numerical plain text ’m’ as seed. Plaintext mapped to random Random chiphertext selection Sized Non overlapping interval via seed “1|| F4 Fig 4: OPM algorithm process · AES Algorithm AES (Advanced Encryption Standard symmetric encryption/decryption algorithm Follo wing Fig.5 shows AES algorit hms struct ure for encry ption and decry ption. Encryption Standard) [11] is a Fig 5. AES 1 2 . . M-1 M NN algorithm. Decryption 41 1 2 3 4 5 . . . N-2 N-1 1 2 3 . . . . N-2 N-1 N
  • 4. International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 E-ISSN: 2321-9637 42 6. RESULT Fig 6(a). User Registration Fig 6(b).User Login Fig 6(c) Searched keyword Fig 6(e). Upload file 7. CONCLUSION Cloud computing is one of the current most important and promising technologies. A data owner can store his data in cloud and user could retrieve data files whenever needed. To retrieve data files correctly we introduce ranked keyword search mechanism. In this
  • 5. International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 E-ISSN: 2321-9637 43 paper we motivate and solve the problem of supporting efficient ranked keyword search for achieving effective utilization of remotely stored encrypted data in Cloud Computing. Then appropriately weaken the security guarantee, resort to the newly developed crypto primitive OPSE, and derive an efficient one-to-many order-preserving mapping function. For future works, a new scheme could be developed the authentication of ranked search results, and the reversibility of our proposed one-to-many order-preserving mapping technique, and searching technique for audio and video. REFERENCES [1] Yanbin Lu and Gene Tsudik,”Enhancing Data Privacy in the Cloud”,University of California, Irvine [2] C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, ”Secure ranked keyword search over encrypted cloud data”,in Proc. of ICDCS’10,2010. [3] Kiruthigapriya Sengoden, Swaraj Paul , ”Improving the Efficiency of Ranked keyword Search over Cloud Data”, International Journal of Advanced Research in Computer Engineering and Technology (IJARCET) Volume 2,Issue 3, March 2013. [4] Ms Mayura R. Girme, Prof.G.M. Bhandari, ”Efficient Secure Ranked keyword search Algorithms over outsource cloud data”, International Journal of Emerging Trends and Technology in Computer Science (ISSN 2278- 6856), Volume 2, Issue 5,September- October 2013 [5] Pooja Shah, Gopal Pandey,”Keyword Searching techniques for Encrypted Cloud data”, Department of Information Technology, Shantilal Shah Engineering College,Bhavnagar [6] D. Song, D. Wagner, and A. Perrig, ”Practical techniques for searches on encrypted data”,in Proc. of IEEE Symposium on Security and Privacy’00, 2000. [7] E.-J. Goh,”Secure indexes”, Cryptology ePrint Archive, Report 2003/216. [8] D. Boneh, G. D. Crescenzo, R. Ostrovsky, and G. Persiano, ”Public key encryption with keyword search”,in Proc. of EUROCRYP’04,volume 3027 of LNCS. Springer,2004. [9] Cong Wang, Ning Cao, Kui Ren , Wenjing Lou, Senio(2012),”Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data”, IEEE Transactions on Parallel and Distributed systems, VOL.23,NO.8. [10]Alexandra Boldyreva, Nathan Chenette, Younho Lee, and Adam O’Neill Georgia,”Order- Preserving Symmetric Encryption”,in Proc. of Eurocrypt’09, volume 5479 of LNCS. Springer 2009. [11] http://www.facweb.iitkgp.ernet.in/sourav/AES.pdf