application of fuzzy multi-keyword search and … · keyword fuzzy search. however, those existing...

APPLICATION OF FUZZY MULTI-KEYWORD SEARCH AND

RERANKING LOGIC FOR OUTSOURCED CLOUD DATA

Ms. R.Chitra1, V. K. Sanjay kumar

2, M. Thilak

2, A. R. keerthi

2

1Assi.Professor, Department of Computer Science and Engineering, Velammal Institute of Technology, Chennai

2Student, Department of Computer Science and Engineering, Velammal Institute of Technology, Chennai

Corresponding Author Address:

A. R. keerthi

Student Department of Computer Science and Engineering,

Velammal Institute of Technology,

Chennai, India.

ABSTRACT

In this module, provisions for secure data sharing by a Data Owner to a Cloud System are

created. A Data owner can register with the application, after registering he/she could upload

an encrypted file to the cloud. The Data Owner can also delete a file from the cloud. In

addition to that, provisions for the Data Owner to make a request for a private key from a

Trusted Third Party will also be implemented. Algorithm for making a fuzzy search of the

Cloud files is implemented. The Client can make a search of the existing Cloud files for any

intended topics. Even if the Client commits spelling mistakes while typing the search key, the

algorithm will make probable matches and produce a matching files list .algorithm for

making multi-keyword searching logic is implemented. The output generated by the Fuzzy

Logic Implementation is the input for Multi-Keyword search algorithm. The application

searches based upon the phrase matching the search term and generates newer list of

matching files which can be viewed by the Client. A Trusted Third Party Auditor(TPA) is

created and his primary task is to Reassign Keys for the security revoked files. And in

addition to that, the TPA also generates keys for the Data Owner. On request the key will be

sent to a Data Owner by the TPA.

KEYWORDS: Fuzzy Logic Multi key-word Search

INTRODUCTION

Due to the flexibility and economic savings offered by the cloud server, the users have been

motivated to outsource the management of their data to the cloud. However, because of

privacy concerns, data owners encrypt sensitive data prior to outsourcing, which in turn

makes data utilization a challenging problem. Thus, development of an efficient privacy

preserving search system over encrypted cloud data is of great importance. The most

common search methods retrieve files using keywords instead of retrieving all the encrypted

files back. To securely searching over encrypted data, the data owner usually builds an

encrypted index structure using the extracted keywords from the data files and a

corresponding index-based keyword matching algorithm and subsequently outsources both

the encrypted data and this constructed index structure to the cloud. When searching the files,

International Journal of Scientific Research in Engineering (IJSRE) Vol. 1 (4), April, 2017

IJSRE Vol. 1 (4), April, 2017 www.ijsre.in Page 68

the cloud server integrates the trapdoors of the keywords with the index information and then

returns the corresponding files to the data users. Moreover, the data owner can share their

data with a large number of users which requires the cloud server to have the ability to meet a

large amount of requests with effective data retrieval services. One effective method for

solving this problem is ranking the results and sending back the top-K files to the data user,

rather than all of the relevant files.

This method can dramatically reduce the communication overhead and still meet user’s

demand. However, such a ranking operation should not leak any other information related to

the keywords.

LITERATURE SURVEY

W. Sun proposed a way to Privacy-preserving multi keyword fuzzy search over encrypted

data in the cloud although encryption helps protecting user data confidentiality, it leaves the

well-functioning yet practically-efficient secure search functions over encrypted data a

challenging problem

Disadvantage: Encryption with Single Keyword

N. Cao, C. Wang proposed a way to, Privacy-preserving multi-keyword ranked search over

encrypted cloud data 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.

EXISTING SYSTEM

The majority of the existing techniques are focusing on multi-keyword exact match or single

keyword fuzzy search. However, those existing techniques find less practical significance in

real-world applications compared with the multi keyword fuzzy search technique over

encrypted data. The first attempt to construct such a multi-keyword fuzzy search scheme was

reported by Wang who used locality-sensitive hashing functions and Bloom filtering to meet

the goal of multi-keyword fuzzy search. Nevertheless, Wang’s scheme was only effective for

a one letter mistake in keyword but was not effective for other common spelling mistakes.

Moreover, Wang’s scheme was vulnerable to server out-of-order problems during the ranking

process and did not consider the keyword weight. In this paper, based on Wang scheme, we

propose an efficient multi keyword fuzzy ranked search scheme based on Wang scheme that

is able to address the aforementioned problems.

First, we develop a new method of keyword transformation based on the unigram, which will

simultaneously improve the accuracy and creates the ability to handle other spelling mistakes.

In addition, keywords with the same root can be queried using the stemming algorithm.

Furthermore, we consider the keyword weight when selecting an adequate matching file set.

Experiments using real-world data show that our scheme is practically efficient and achieve

high accuracy.



PROBLEM DEFINITION

1. System Model

The system model thought-about during this paper consists of 3 entities: the info owner, the

info user, and the cloud server. The data owner outsources a large size of document

assortment DC = d1, d2, … dm within the encrypted kind C= c1, c2, … cm, alongside

associate h-level searchable index tree I generated from DC, to the cloud server.

2. Threat Model

We assume that the cloud server acts in an “honest but-curious” manner, which is also

employed by related works on secure cloud data search.

PROPOSED SYSTEM:

We propose a multi-keyword fuzzy ranked search scheme based on Wanget al.’s scheme.

Concretely, we develop a novel method of keyword transformation and introduce the

stemming algorithm. With these two techniques, the proposed scheme is able to efficiently

handle more misspelling mistake. Moreover, our proposed scheme takes the keyword weight

into consideration during ranking. Like Wang et al.’s scheme, our proposed scheme does not

require a predefined keyword set and hence enables efficient file update too. We also give

thorough security analyses and conduct experiments on real world data set, which indicates

the proposed scheme’s potential of practical usage. Our future works can be summarized as

follows:

1. Fuzzy hierarchal search supporting dynamic update: although our theme during this paper

will support update, we have a tendency to didn't come through the best state as a result

of the keyword weight. we are going to develop how to mirror the keyword weight and

modify update.

2. linguistics search: exactly, once the user’s question may be a sentence, we are able to

extract the attributes of a sentence, and so categorical the link between attributes and

search although the attributes.

3. Multi-data owner scheme: these days, several works were chiefly that specialize in the

cases of single information owner and thus not effective for multi-data owner. Note that

multi data owner theme has additional realistic significance.

4. Verification: Verification may be a hot topic in cloud computing. Reference projected a

results verification search theme over encrypted cloud information. And Wang et al.

conferred a unique verifiable auditing theme for outsourced info supported Bloom filter.

we are going to learn additional concerning these and style a verifiable search theme over

encrypted cloud information.

RESULTS: The setup of the portals with their description is as follows

A. Efficiency

1) Trapdoor generation: The trapdoor generation method contains 3 major steps: stemming,

the Bloom filter generation and also the secret writing .shows the whole time of trapdoor

stemming and Bloom filter generation. The generation time augmented linearly with

relevance the quantity of the inserted keywords. Because the number of keywords grew, the

trapdoor generation time additionally augmented.



2) Index construction: The index construction time was a similar as that of trapdoor

generation. as a result of the stemming and Bloom filter generation were linear within the

range of the keywords, the index vector generation time may well be giant, however it

absolutely was simply a one-time effort .shows that the secret writing time is linear within the

size of files as a result of the index structure we tend to created was a per file primarily based

index.

CONCLUSION:

It is ensured that information owner will transfer knowledge within the cloud in Associate in

Nursing encrypted thanks to security to information conjointly shopper to knowledge owner

will download knowledge from the cloud below permission from data owner with the key

client will search the information supported the keyword it show the information titles that

contain the keyword however it doesn't show the important identity of the data Hence it

ensures data integrity

REFERENCES:

1. B. Wang, S. Yu, W. Lou, and Y. T. Hou, “Privacy-preserving multikeyword fuzzy search

over encrypted data in the cloud,” in Proc. IEEE INFOCOM, Apr./May 2014, pp. 2112–

2120.

2. N. Cao, C. Wang, M. Li, K. Ren, and W. Lou, “Privacy-preserving multi-keyword ranked

search over encrypted cloud data,” in Proc. IEEE INFOCOM, Apr. 2011, pp. 829–837.

3. W. Sun et al., “Privacy-preserving multi-keyword text search in the cloud supporting

similarity-based ranking,” in Proc. 8th ASIACCS, 2013, pp. 71–82.

4. Z. Xu, W. Kang, R. Li, K. C. Yow, and C.-Z.Xu, “Efficient multikeyword ranked query

on encrypted data in the cloud,” in Proc. 18th

IEEE Int. Conf. Parallel Distrib. Syst., Dec.

2012, pp. 244–251.

5. Z. Xia, X. Wang, X. Sun, and Q. Wang, “A secure and dynamic multikeyword ranked

search scheme over encrypted cloud data,” IEEE Trans. Parallel Distrib. Syst., vol. 27,

no. 2, pp. 340–352, Feb. 2016, doi: 10.1109/TPDS.2015.2401003.

6. Z. Fu, J. Shu, X. Sun, and D. Zhang, “Semantic keyword search based ontrie over

encrypted cloud data,” in Proc. 2nd Int. Workshop Security Cloud Comput., Kyoto, Japan,

Jun. 2014, pp. 59–62.

7. Z. Fu, J. Shu, X. Sun, and N. Linge, “Smart cloud search services: Verifiable keyword-

based semantic search over encrypted cloud data,” IEEE Trans. Consum. Electron., vol.

60, no. 4, pp. 762–770, Nov. 2014.

8. M. Chuah and W. Hu, “Privacy-aware bedtree based solution for fuzzy multi-keyword

search over encrypted data,” in Proc. 31st Int. Conf. Distrib.Comput. Syst. Workshops

(ICDCSW), Jun. 2011, pp. 273–281.

9. C. Liu, L. Zhu, L. Li, and Y. Tan, “Fuzzy keyword search on encrypted cloud storage

data with small index,” in Proc. ICCCIS, Sep. 2011, pp. 269–273.

10. R. Curtmola, J. Garay, S. Kamara, and R. Ostrovsky, “Searchable symmetric encryption:

Improved definitions and efficient constructions,” inProc. CCS, 2006, pp. 79–88.



application of fuzzy multi-keyword search and … · keyword fuzzy search. however, those existing...

Documents