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SSPM’sSOMESHWAR ENGINEERING COLLEGE
SOMESHWARNAGAR Department of Computer Engineering
Seminar On
“Privacy-preserving Multi-keyword Fuzzy Search Over Encrypted Data In The Cloud”
Guide Name: Presented By, Prof. Shinde V.D. Miss-Limbarkar Archana
Roll no:-22
17/03/16 1
CONTENTS
IntroductionProblem definitionExisting SystemLiterature SurveyDisadvantages of Existing SystemArchitectureMethodologyMathematical ModelAdvantages/FeaturesConclusionReferences
17/03/16 2
INTRODUCTION
Cloud Computing
Scalable
Elastic Storage
Computation Resources
Outsourcing Data Services.
17/03/16 3
PROBLEM DEFINITION
High privacy
Keyword collection
Search and a trapdoor
17/03/16 4
EXISTING SYSTEM
Cloud computing
Ranking to meet the effective data retrieval need.
Searchable encryption
Cloud computing contains more private and sensitive information’s such as emails,
government documents, personnel records
MRSE technique
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LITERATURE SURVEY
17/03/16 6
DISADVANTAGES OF EXISTING SYSTEM
Secure ranked search over encrypted data problem.
Efficient encrypted data search mechanism.
Privacy problem.
Time delay.
17/03/16 7
ARCHITECTURE
17/03/16 8Fig-System Architecture of Search over Encrypted data on cloud computing
METHODOLOGY
1.KeyGen(m)-Key Generation
2.Index Enc(SK; I)-Index Encryption
3.Query Enc(SK;Q)-Query Encryption
4.BuildIndex(D; SK; l)-Index Building
5.Trapdoor(Q; SK)-Trapdoor Generation
6.Search(EncSK(Q);EncSK(ID))-Searching
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MATHEMATICAL MODEL
Let us consider S as a set of inputs.
S= { }
INPUT:
Identify the inputs as keyword transformation
information
F= {f1, f2, f3 ....., fn| ‘F’ as set of functions to execute the process}
I= {i1, i2, i3…|’I’ sets of inputs to the function set}
O= {o1, o2, o3….|’O’ Set of outputs from the function sets}
S= {I, F, O}
I = {keyword transformation information}
O = {Index,Query}
F = {Build index,trapdoor generation}
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ADVANTAGES
Multi-Keyword Fuzzy Search
Privacy Guarantee
Result Accuracy
No Predefined Dictionary
Security
Performance
17/03/16 11
FEATURES
Efficiency
Enhanced Scheme
F-measure
Security Analysis of Enhanced Scheme
Performance Analysis
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CONCLUSION
In this seminar, we tackled the challenging multi-keyword fuzzy search problem over the encrypted data.
We proposed and integrated several innovative designs to solve the multiple keywords search and the fuzzy search problems simultaneously with high efficiency.
17/03/16 13
REFERENCES
1. D. Song, D. Wagner, and A. Perrig, “Practical techniques for searches on encrypted
data,” S&P 2000, vol. 8, pp. 44–55, 2000.
2.W. Sun, B. Wang, N. Cao, M. Li, W. Lou, T. Hou, and H. Li, “Privacypreserving multi-
keyword text search in the cloud supporting similaritybased ranking,” in ASIACCS
2013, May 2013.
3.D. Boneh, G. D. Crescenzo, R. Ostrovsky, and G. Persiano, “Public key encryption with
keyword search,” EUROCRYPTO 2004, pp. 506–522,2004.
4. N. Cao, C. Wang, M. Li, K. Ren, and W. Lou, “Privacy-preserving multi-keyword
ranked search over encrypted cloud data,” INFOCOM 2011, pp. 829–837, 2011
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CONTINUES….
1.Y. Hwang and P. Lee, “Public key encryption with conjunctive keyword
search and its extension to a multi-user system,” Pairing 2007, pp. 2–
22,2007.
2. D. Boneh and B. Waters, “Conjunctive, subset, and range queries on
encrypted data,” Theory of Cryptography, vol. 4392, pp. 535–554, 2007.
3.P. Golle, J. Staddon, and B. Waters, “Secure conjunctive keyword search
over encrypted data,” ACNS 2004, vol. 3089, pp. 31–45, 2004.
4.C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, “Secure ranked keyword
search over encrypted cloud data,” ICDCS 2010, pp. 253–262, 2010.17/03/16 15
QUESTIONS???
17/03/16 16
THANK YOU…!!!
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