fuzzy

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Fuzzy Keyword Search over

Encrypted Data in Cloud Computing

Abstract:

As Cloud Computing becomes prevalent, more and more

sensitive information are being centralized into the cloud. Although

traditional searchable encryption schemes allow a user to securely search

over encrypted data through keywords and selectively retrieve les of

interest, these techniques support only exact keyword search. n this

paper, for the rst time we formalize and solve the problem of e!ective

fuzzy keyword search over encrypted cloud data while maintaining

keyword privacy. "uzzy keyword search greatly enhances system usability

by returning the matching les when users# searching inputs exactly

match the predened keywords or the closest possible matching les

based on keyword similarity semantics, when exact match fails. n our

solution, we exploit edit distance to quantify keywords similarity and

develop two advanced techniques on constructing fuzzy keyword sets,

which achieve optimized storage and representation overheads. $e

further propose a brand new symbol%based trie%traverse searching

scheme, where a multi%way tree structure is built up using symbolstransformed from the resulted fuzzy keyword sets. &hrough rigorous

security analysis, we show that our proposed solution is secure and

privacy%preserving, while correctly realizing the goal of fuzzy keyword

search. 'xtensive experimental results demonstrate the e(ciency of the

proposed solution.

Algorithm / echni!ue used:

)tring *atching Algorithm

Algorithm Description:

&he approximate string matching algorithms among them can be

classied into two categories+ on%line and o!%line. &he on%line techniques,

performing search without an index, are unacceptable for their low search

e(ciency, while the o!%line approach, utilizing indexing techniques,makes it dramatically faster. A variety of indexing algorithms, such as

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su(x trees, metric trees and q%gram methods, have been presented. At

the rst glance, it seems possible for one to directly apply these string

matching algorithms to the context of searchable encryption by

computing the trapdoors on a character base within an alphabet.

owever, this trivial construction su!ers from the dictionary and statisticsattacks and fails to achieve the search privacy. An instance M of the data

type string-matching is an ob-ect maintaining a pattern and a string. t

provides a collection of di!erent algorithms for computation of the exact

string matching problem. 'ach function computes a list of all starting

positions of occurrences of the pattern in the string.

System Architecture:

E"isting System: &his straightforward approach apparently provides fuzzy keyword search

over the encrypted les while achieving search privacy using the

technique of secure trapdoors. owever, this approaches serious

e(ciency disadvantages. &he simple enumeration method in constructing

fuzzy key%word sets would introduce large storage complexities, which

greatly a!ect the usability.

"or example, the following is the listing variants after a substitution

operation on the rst character of keyword

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CAS#E: $AAS#E% &AS#E% DAS#E% 'AS#E%

(AS#E)*

+roposed System:

,ain ,odules:

-* .ildcard &ased echni!ue

0* 1ram 2 &ased echni!ue

3* Symbol &ased rie traverse Search Scheme

-* .ildcard &ased echni!ue:

n the above straightforward approach, all the variants of thekeywords have to be listed even if an operation is performed at the same

position. ased on the above observation, we proposed to use an wildcardto denote edit operations at the same position. &he wildcard%based fuzzyset edits distance to solve the problems.

"or example, for the keyword CA)&/' with the pre%set edit distance 0, itswildcard based fuzzy keyword set can be constructed as

SCAS#E% - 4 $CAS#E% 5CAS#E%5AS#E% C5AS#E% C5S#E% CAS#5E% CAS#5%CAS#E5)*

Edit Distance:

a. )ubstitutionb. 1eletionc. nsertion

a2 Substitution + changing one character to another in a word3

b2 Deletion + deleting one character from a word3

c2 6nsertion+ inserting a single character into a word.

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0* 1ram &ased echni!ue:

Another e(cient technique for constructing fuzzy set is based on grams. &he gram of a string is a substring that can be used as a signature fore(cient approximate search. $hile gram has been widely used for

constructing inverted list for approximate string search, we use gram forthe matching purpose. $e propose to utilize the fact that any primitiveedit operation will a!ect at most one specic character of the keyword,leaving all the remaining characters untouched. n other words, therelative order of the remaining characters after the primitive operations isalways kept the same as it is before the operations.

"or example, the gram%based fuzzy set )CA)&/', 0 for keyword CA)&/'can be constructed as

$CAS#E% CS#E% CA#E% CAS#E% CASE% CAS#% AS#E)*

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3* Symbol &ased rie traverse Search Scheme

&o enhance the search e(ciency, we now propose a symbol%basedtrie%traverse search scheme, where a multi2way tree is constructed forstoring the fuzzy keyword set over a nite symbol set. &he key ideabehind this construction is that all trapdoors sharing a common prex mayhave common nodes. &he root is associated with an empty set and the

symbols in a trapdoor can be recovered in a search from the root to theleaf that ends the trapdoor. All fuzzy words in the trie can be found by adepth%rst search.

n this section, we consider a natural extension from the previous single%user setting to multi%user setting, where a data owner stores a lecollection on the cloud server and allows an arbitrary group of users tosearch over his le collection.

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System 7e!uirements:

Hardware Requirements:

• System : Pentium IV 2.4 GHz.

• Hard Disk : 40 GB.

• Floy Dri!e : ".44 #$.

• #onitor : "% VG& 'olour.

• #ouse : (o)ite*+.

• ,am : %"2 #$.

Software Requirements:

• -eratin) system : /indos 1P.

• 'odin) (an)ua)e : D- 3

• Data Base : S5( Ser!er 200%

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Conclusion:

-* n this paper, for the rst time we formalize and solve the problem of

supporting e(cient yet privacy%preserving fuzzy search for achieving

e!ective utilization of remotely stored encrypted data in Cloud

Computing.

4. $e design two advanced techniques 5i.e., wildcard%based and gram%based techniques2 to construct the storage%e(cient fuzzy keyword sets byexploiting two signicant observations on the similarity metric of edit

distance.

6. ased on the constructed fuzzy keyword sets, we further propose abrand new symbol%based trie%traverse searching scheme, where a multi%way tree structure is built up using symbols transformed from the resultedfuzzy keyword sets.

7. &hrough rigorous security analysis, we show that our proposed solutionis secure and privacy% preserving, while correctly realizing the goal of fuzzy keyword search. 'xtensive experimental results demonstrate thee(ciency of our solution.

fuzzy

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