With the evolution in Cloud Computing more and more sensitive data is being incorporate into the cloud. To ensure security and privacy these data are first encrypted before being uploaded onto the cloud servers thus making search a complicated task. Although in traditional cloud computing encryption searching schemes allows user to search encrypted data through keywords securely. These techniques employed exact keyword search and will fail if there are any morphological variants or spelling errors. This leads to low in efficiency and also affects system usability very badly. Fuzzy keyword search increases the system usability by allowing matching the exact or closet match text to the stored keywords and retrieving the approximate closest results. We shall be using edit distance to quantify keywords. We ensure the privacy of the data against unauthenticated users by encrypting the data using AES encryption before uploading to the cloud servers. We tend to resolve this problem by using a cloud server and employing fuzzy keyword search based on N grams. Thus, efficiency of our proposed system would be demonstrated through experimental results

1. PROJECT ON FUZZY KEYWORD SEARCH OVER
ENCRYPTED DATA IN CLOUD COMPUTING
MOHAMMED AHMED HUSSAIN
ASIM AHMED KHAN JAWAAD
MOHAMMAD ASIF

2. ABSTRACT
What is fuzzy keyword search?
 Fuzzy Search: approximate string matching
Ex. Languaje will be corrected to language
Scenario:
1. User want search keyword language
2. User misspelled it as languaje and clicked on search button
3. Data in the database is in encrypted form.
4. Now search the encrypted data for inputted keyword languaje.
5. Which will converted to language and display result.
6. This is the technique which will help us to match the keyword languaje with
encrypted keywords in the database.

3. EXISTING SYSTEM
1. To ensure security and privacy data are first encrypted before being uploaded onto the
cloud servers.
2. These techniques support only conventional Boolean keyword search, without capturing
any relevance of the files in the search result.
3. In traditional cloud computing encryption searching schemes allows user to search
encrypted data through keywords securely.
4. These techniques employed exact keyword search and will fail if there are any
morphological variants or spelling errors.
5. This leads to low in efficiency and also affects system usability very badly.
Disadvantages
6. Single keyword search
7. Exact match
8. Less efficient

4. PROPOSED SYSTEM
1. This project defines and solve the problem of multi-keyword ranked search over encrypted
cloud data
2. It preserving strict system-wise privacy in cloud computing paradigm.
3. It increases the system usability by allowing matching the exact or closet match text to the
stored keywords and retrieving the approximate closest results.
4. By using edit distance to quantify keywords and ensure the privacy of the data against
unauthenticated users
5. Encrypting the data using AES encryption before uploading to the cloud servers.
6. By using a cloud server and employing fuzzy keyword search based on N grams.
7. Efficiency of our proposed system would be demonstrated through experimental results.

5. ENCRYPTION TECHNIQUES
1. AES is a block cipher technique with block size of 128 bits.
2. To encrypt our data by using AES with 128-bit key length.
3. For 128-bit keys the encryption process consists of 10 rounds.
4. In each case all the rounds are identical other than the last round.

6. N-GRAMS TECHNIQUE
1. Suppose we have to store keyword: “language”
2. N-grams: lan ang ngu gua uag age
3. Encrypted n-grams: thr yu7 tf5 7yt lk8 eer
4. Storing thr into index_0 table (1st table)
5. Storing yu7 into index_1 table (2nd table)
6. Storing tf5 into index_2 table (3rd table)
7. Storing 7yt into index_3 table and so on….
8. Rather than storing all n-grams into single table we are storing the first n-gram in first
table, second n-gram in second table and so on.
9. This will reduce the number of comparisons required to match the n-grams and hence
faster the search results.

7. WILDCARD-BASED TECHNIQUE
1. Try to generate smaller fuzzy sets
2. Wildcards
●
Denote operations at the same position
3. Wildcard-based fuzzy set
4. Swi,d = {S’wi,0,S’wi,1,...,S’wi,d}
5. S’wi,τ is the set of words w’i with τ wildcards
6. Example
7. w = CASTLE,τ = 1
8. SCASTLE,1 = {CASTLE, CASTLE, ASTLE,∗ ∗ C ASTLE,C STLE,...,∗ ∗
CASTL E,CAST E,CASTLE }∗ ∗ ∗

8. SOFTWARE REQUIREMENTS
1. PHP
2. MySQL
3. Codeigniter PHP framework
4. HTML, CSS
HARDWARE REQUIREMENTS
1. Processor: Pentium IV 2.4 GHz.
2. Hard Disk : 40 GB
3. Monitor : 15 VGA Colour.
4. Ram: 512 Mb.

9. THE WORKING OF PROJECT

10. DATAFLOW DIAGRAMS
 Level 0 DFD

11.  Level 1 DFD

12. UML DIAGRAMS

13. CLASS DIAGRAM

14. USE CASE DIAGRAM

15. SEQUENCE DIAGRAM

16. ACTIVITY DIAGRAM

17. COLLABORATION DIAGRAM

18. STATE CHART DIAGRAM

19. COMPONENT DIAGRAM

20. DEPLOYMENT DIAGRAM

21. RELATIONAL DATABASE MODEL

22. GUI DESIGN

23. CONCLUSION
1. In this project, the problem of supporting efficient yet privacy-preserving fuzzy
search for achieving effective utilization of remotely stored encrypted data in
cloud computing is solved.
2. Two advanced techniques were designed to construct the storage-efficient fuzzy
keyword sets by exploiting two significant observations on the similarity metric
of edit distance.
3. Based on the constructed fuzzy keyword sets, a brand-new symbol-based trie-
traverse searching scheme is proposed.
4. Where a multi-way tree structure is built up using symbols transformed from the
resulted fuzzy keyword sets.
5. It is shown that our proposed solution is secure and privacy- preserving, while
correctly realizing the goal of fuzzy keyword search.

24. REFERENCE
1. Fuzzy keyword search over encrypted data in cloud computing" by C. Anuradha.
2. Implementation of fuzzy keyword search over encrypted data in cloud computing" by d.
Vasumathi.
3. Fuzzy keyword search over encrypted data in cloud computing", illinois institute of
technology, issn: 2321-8134.
4. Practical techniques for searches on encrypted data" by d. Song, A. Perrig. In IEEE, 2000.
5. Privacy preserving keyword searches on remote encrypted data" by y. C. Chang in ACNS,
2005.
6. Overview on selective encryption of image and video" by a massoudi in eurasip, 2008.
7. Efficient interactive fuzzy keyword search "by j. Feng, G. Li in WWW, 2009.

25. THANKYOU!