Fuzzy Keyword Search over Encrypted Data in Cloud Computing

ByMr.P.Durgaprasad

09d41d5807M.Tech[cse]

Sri Indu College of Engineering and Technology

Contents

• Objective• Basic definitions• Existing system• Proposed system• Modules in the project• Algorithms used• UML diagrams• Output screens• Future enhancement• Conclusion• References

Objective

• Privacy- preserving fuzzy keyword search in Cloud Computing.

• Effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy.

Basic Definitions

Cloud

• Collection of sources of services like servers. Medium is Internet.

• Services are utilized through internet from geographically dispersed locations

Cloud Computing

• Cloud Computing (CC)is all about implementing process online instead in your local gadget.

• Data and processes could be done online without the need of any local software or client.

• As long as the user knows the process and have the right security credentials, he could access the system and make the necessary changes.

Fuzzy Logic

• Fuzzy logic is a form of many-valued logic; it deals with reasoning that is approximate rather than fixed and exact.

• Fuzzy logic has been applied to many fields, from control theory to artificial intelligence.

CryptographyEncryption-Decryption

• Encryption :Plain or clear text is changed to cipher text using a key.

• Decryption : Cipher text is changed to plain text using a key.

• Crypto algorithm-Algorithms used in cryptography.

Existing System

• The approach provides fuzzy keyword search over the encrypted files while achieving search privacy using the technique of secure trapdoors.

• This approaches efficiency disadvantages- The enumeration method in constructing fuzzy key-word

sets would introduce large storage complexities.Greatly affect the usability.

• For example, the following is the listing variants after a substitution operation on the first character of keyword

• CASTLE: {AASTLE, BASTLE, DASTLE, YASTLE, ZASTLE}.

Proposed System 3 techniques

• Fuzzy Keyword Search over Encrypted Data in Cloud Computing system is designed basically in Three Modules

• Wildcard – Based Technique• Gram - Based Technique• Symbol – Based Tree – traverse Search Scheme

MD5 Algorithm• The MD5 Message-Digest Algorithm is a widely used

cryptographic hash function that produces a 128-bit (16-byte) hash value.

• MD5 has been employed in a wide variety of security applications, and is also commonly used to check.

• The 128-bit (16-byte) MD5 hashes (also termed message digests) are typically represented as a sequence of 32 hexadecimal digits. The following demonstrates a 43-byte ASCII input and the corresponding MD5 hash:

MD5("The quick brown fox jumps over the lazy dog") = 9e107d9d372bb6826bd81d3542a419d6

www.md5encryption.com

MD5 Encryption

.Net Class for crypto process

• “MD5CryptoServiceProvider”

• “TripleDESCryptoServiceProvider”

for encryption and decryption.

String Matching Algorithm

Definition • An instance M of the data type string_matching is an

object maintaining a pattern and a string. It provides a collection of different algorithms for computation of the exact string matching problem. Each function computes a list of all starting positions of occurrences of the pattern in the string.

• The algorithms can be called explicitly by their name or implicitly by making an algorithm the "current" algorithm (specified by the setAlgorithm-method) and

• using functions getFirstOccurence(), getNextOccurence(), and getAllOccurences().

• The string matching algorithms among them can be classified into two categories:

on-line off-line

• The on-line techniques, performing search without an index, are unacceptable for their low search efficiency,

• while the off-line approach, utilizing indexing techniques, makes it dramatically faster.

Modules in the project

There are 3 modules

Wildcard – Based TechniqueGram – Based TechniqueSymbol – Based Trie – traverse Search

Scheme

Wildcard – Based Technique:

• We proposed to use a wildcard to denote edit operations.

• The wildcard-based fuzzy set edits distance to solve the problems.

• For example, for the keyword CASTLE with the pre-set edit distance 1, its wildcard based fuzzy keyword set can be constructed as

• SCASTLE, 1 = {CASTLE, *CASTLE,*ASTLE, C*ASTLE, C*STLE, CASTL*E, CASTL*, CASTLE*}.

Edit Distance:

• Substitution

• Deletion

• Insertion

• Substitution : changing one character to another in a word;

• Deletion : deleting one character from a word;

• Insertion: inserting a single character into a word.

Gram – Based Technique

• Technique for constructing fuzzy set is based on grams. • The gram of a string is a substring that can be used as

a signature for efficient approximate search.• Gram used for constructing a list for approximate string

search• Any primitive edit operation will affect at most one

specific character of the keyword, leaving all the remaining characters untouched.

For example, the gram-based fuzzy set SCASTLE, 1 for keyword CASTLE can be constructed as

• {CASTLE, CSTLE, CATLE, CASLE, CASTE, CASTL, ASTLE}.

Symbol – Based Trie – traverse Search

Scheme • we now propose a symbol-based trie-traverse

search scheme, where a multi-way tree is constructed for storing the fuzzy keyword set.

• The key idea behind this construction is that all trapdoors sharing a common prefix may have common nodes.

• The root is with an empty set and the symbols in a trapdoor can be recovered in a search from the root to the leaf that ends the trapdoor.

Design of UML diagrams

• Usecase diagram

User

Admin

Upload files

Fuzzy search

Register

Download files

Manage all details

If user exists

If user doesnot exists

Class diagram

Upload files

fileidfilenamefiles

upload()

Fuzzy search

saerch_idsearchdata

search()insertion()deletion()

Download files

useridusernameaddressemailidmobileno

register()download()

Sequence diagram

User Admin

Server

Upload files

Search files

Retrieve files

Register

Download files

Dataflow DiagramStart

Admin loginUser search

Import filesEnter data to search

Upload filesFuzzy search

DatabaseGet response

User login

If exists

Download filesRegister

End

YesNo

Manage user/filesdetails

Output ScreensHome page

Encryption

Conclusion

• In this project, for the first time we formalize and solve the problem of supporting efficient yet privacy-preserving fuzzy search for achieving effective utilization of remotely stored encrypted data in Cloud Computing.

• We design two advanced techniques (i.e., wildcard-based and gram- based techniques) to construct the storage-efficient fuzzy keyword sets.

Future Enhancements

• We further propose a brand new symbol-based trie-traverse searching scheme, where a multi-way tree structure is built up.

• Through rigorous security analysis, we show that our proposed solution is secure and privacy- preserving, while correctly realizing the goal of fuzzy keyword search. Extensive experimental results demonstrate the efficiency of our solution.