Paper id 28201425 by IJRAT

International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 E-ISSN: 2321-9637

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

PKE

Proposed System Not supported.

Sequential Approach

Yes

Document Index Keyword Filter Secret Key

Yes

Public

Cloud computing

Yes

Private Yes

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 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

Characteristic s Range

Fig 1. System comparative analysis

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, ing, 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 ion 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—a form trapdoor Tw of the keyword w to the cloud server. Upon receiving the he search request Tw, the cloud server is 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.

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 many order-preserving order mapping technique. The resulting design is able to facilitate efficient server-side 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 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

Fig 2. System architecture [2] [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 arches 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

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 system.

encryption key. Ciphertext ’c’ is then chosen by using numerical plain text ’m’ m’ as seed. Plaintext mapped to random Random chiphertext selection Sized Non overlapping interval via seed “1|| F4

1 2 . . M-1 M

1 2 3

1 2 3 . . . . N-2 N-1 N

4 5 . . . N N-2 N N-1

Fig 4: OPM algorithm process • Fig 3. Design process

1. Mathematical Model Design & Algorithms •

Ranking Function- It is used to calculate relevance (frequency) score of keyword.[9] keyword. Score (Q, Fd) =ΣtεQ 1/|Fd|.(1+ln fd,t) .ln(1+N/ft) Parameters • Q - searched keywords; • fd,t - TF of term t in file Fd; • ft - number of files that contain term t; • N -The The total number of files in the collection; • |Fd| -Length of file Fd,

•

AES Algorithm

AES (Advanced Advanced Encryption Standard) Standard [11] is a symmetric encryption/decryption decryption algorithm algorithm. Follo wing Fig.5 shows AES algorit hms struct ure for encry ption and decry ption.

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” “Network” = F1||1; F2||1; F4||1; |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 overlapping interval in range, determined by

Encryption

Decryption Fig 5. AES

International Journal of Research in Advent Technology, Vol.2, No.8, August 2014 E-ISSN: 2321-9637 6.

RESULT

Fig 6(a). User Registration

Fig 6(c) Searched keyword

Fig 6(b).User Login 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 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 22786856), 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,”OrderPreserving Symmetric Encryption”,in Proc. of Eurocrypt’09, volume 5479 of LNCS. Springer 2009. [11] http://www.facweb.iitkgp.ernet.in/sourav/AES.pdf