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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 07 Issue: 04 | Apr 2020 www.irjet.net p-ISSN: 2395-0072
© 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 265
K-Gram based Composite Secret Sign Search over Encrypted Cloud
Information
Aditi Gaur1, Y.Geetha Sai2, Shriya G.N3
1,2,3Student, Dept. of Computer Science and Engineering, SRM Institute of Science and Technology,
Tamil Nadu, India
---------------------------------------------------------------------***----------------------------------------------------------------------
Abstract - A growing number of owners of data has
transferred our data to cloud servers. Cloud data owners
tend to outsource information in an encrypted form for
confidentiality protection purposes. Developing an effective
and reliable search method for cipher-text is therefore
important. One problem is that the relationship between
documents is usually hidden in theencryptionprocess, which
can lead to a substantial deterioration oftheefficiencyofthe
search accuracy. Using the keyword-based app, all access
data from the cloud. The stable multi-keyword ranked cloud
to search for encrypted data, a top-k quest for big data
encryption against breaches of privacy, and attempt to find
an efficient and safe solution to this problem. It provides
open operations such as downloading, removing, adding
information. Using tree structure and nebulous search
method here to retrieve the cloud data. These types of
techniques are used to solve the keyword conjecture attack
problem. This offers transparent operations suchascopying,
deleting, and information adding. The cloud data is
extracted using a tree structureandnebuloussearchmethod
here. These types of strategies are used to solve the problem
of attack by keyword conjecture.
Key Words: Cloud computing, Multi keyword search,
Java, Semantic resemblance, Encryption
1. INTRODUCTION
Cloud computing infrastructure is ground-breaking new
technology and it significantly accelerates the production
of data storage, processing, and delivery on a wide scale.
Nevertheless, as data owners outsource their private data
to public cloud providers that are not within their trusted
management jurisdictions, security and privacy become
major concerns. To avoid leakage of information, sensitive
data must be encrypted. Most existing works find only
queries of single keywords without sufficient ranking
schemes. The keyword dictionary is static withthecurrent
multi-graded search strategy, and cannot be easily
expanded as the number of keywords grows. It also takes
no account of the user behaviour and the frequency of
keyword access. The out-of-order therankingproblemcan
emerge for the query matching result which contains a
large number of documents. This makes it difficult for the
data used to find the subset which most likely meets their
requirements. In this paper, we propose a versatile multi-
keyword query scheme, called MKQE to resolve the above
disadvantages. MKQE significantly decreasestheoverhead
management during the extension of the dictionary
keyword. When generating the query result it takes into
account keyword weights and user access history. Hence,
records that have higher levels of access and that fit more
to the access history of the users get higher rankings in the
corresponding result collection. Thepurposeoftheproject
is to provide users with various types of search options to
get the full number of file searches from the cloud's
encrypted data.
2. RELATED WORK
Using fuzzy search algorithms to upload the file we can
create lots of keywords for each file hereby providing the
statics based on different conditions, we can highlight the
output report of all these enhancedsearchmechanisms.By
providing the statics dependent on various circumstances,
we can highlight the output report of all such enhanced
search mechanisms. Keyword Guessing Attack is going to
happen in this program, the hackers can easily guess the
keyword because they can easilyhack ourcontentfromthe
cloud server. The current search method can only provide
the result based on the matching framework for Boolean
keywords, meaning that the environment would consider
the exact file name exactly the same as the keyword that
the file would be retrieved from the server, it will not have
any search results for misspelled keywords. And the new
search system never produces results based on related
keywords. Using fuzzy search algorithms to upload the file
we can create lots of keywords for each file hereby
providing the statics based on a differentcondition,wecan
highlight the output report of all these enhanced search
mechanisms. By providing the statics dependent on
various circumstances, we can highlight the output report
of all such enhanced search mechanisms.
3. LITERATURE SURVEY
a. Title: Practical technological searches on encrypted
data
Author: D. X. Song, D. Wagner, and A. Perrig
Year: 2000
Description: To that the protection and privacy risks, it is
beneficial to store data on data storage servers such as
mail servers and file servers in encryptedform.Ciphertext;
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 07 Issue: 04 | Apr 2020 www.irjet.net p-ISSN: 2395-0072
© 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 266
provide isolation of the search query, meaning that the
untrusted server can't know more about theplaintextthan
the search result; provide controlled search so that the
untrusted server can learn something more about the
plaintext. The algorithms we present are simple, fast (the
encryption and searchalgorithmsonlyrequireO(n)stream
cipher and block cipher operations for a document of
length n), and add almost no overhead space and
communication and are therefore practical to use
nowadays. Yet this typically means one hastocompromise
protection features. For example, if a client needs only
documents containing those terms to be retrieved, it was
not previously understood how to allow the data storage
server to conduct the search and address the question
without sacrificing data confidentiality. Within this paper,
we define our cryptographic schemes for the search
problem on encrypted data and providesecurity proofsfor
the resulting cryptosystems. There are a number of
important they are known to be secure: they provide
known confidentiality for encryption, in the sense that the
untrusted server cannot learn more about the plaintext
when only provided.
b. Title: privacy synonym based fuzzy multi keyword
graded search over encrypted cloud
Author: B.Wang, S.Yu, W. Lou, and Y. T. Hou
Year: 2014
Description: Cloud Storage is one of the most commonly
used cloud technologies at this time. As cloud use
increases, sensitive and personal data are also outsourced
which makes it necessary to protecttheconfidentialityand
integrity of this data. A simple way to secure data is to
encrypt it before outsourcing, but the recovery of the
necessary files from the encrypted cloud becomes a
problem involving searching through the encrypted data.
Different schemes have been proposed to fix this issue of
searching over encrypted cloud data, but none of the
current schemes offer ideal user search experience that
Plaintext search. In this paper, we suggest privacy search
meaning Fuzzy Multi-Keyword Ranked Search over
Encrypted Cloud Data, a plan of action that enhances the
user search experience to the greatest level by offering
multi-keyword searches based on both fuzzy and
synonymous, thus bringing encrypted search experience
closer to free search engines for text.Inaddition,byusinga
binary tree-based dynamic index, the scheme increases
index generation time and search the time relative to
existing schemes. Experimental findings reflect the
effectiveness of this proposed scheme as it decreases the
search time, i.e. the time to locate the required data, by 90
percent and minimizes the overhead of database updates
when new files need to be uploaded (database generation
time)Compared with current effective indexing schemes
for similar datasets in the literature. To this point, search
time optimization along with index generation time was
not done before.
c.Title: Similarity over outsourced cloud data achieving
used and privacy secured
Author: C.Wang, K. Ren, S. Yu, and K. M. R. Urs
Year: 2012
Description: As the data generated by individuals and
companies needing to be processed and used is growing
rapidly, data owners are encouraged to outsource their
complex local data management systems to the cloud for
their tremendous versatility and economical savings.
Nevertheless, because sensitive cloud data that need to be
encrypted before outsourcing, which obsolescence the
conventional data management service basedonplaintext
keyword search, how privacy-assured usage mechanisms
for outsourced cloud data are therefore of paramount
importance. Considering the vast number of on-demand
data users and the massive volume of outsourceddata files
in the cloud, the issue is especially daunting because it is
incredibly difficult to satisfy the realistic performance
criteria, device accessibility, andusersearchexperiences at
the highest level. In this paper, we discuss the question of
searching for stable and efficient similarity over
outsourced cloud data. Similarity search is a fundamental
and powerful method commonly used in the retrieval of
plaintext content, but not quite explored in the encrypted
data domain. First, our mechanism architecture takes
advantage of a suppressing technique to create storage-
efficient keyword similarity from a given document set,
editing distance as the similarity metric. We then create a
private tire-traverse search index based on that, and
display it correctly achieves the given search similarity
functionality with constant search time complexity. Under
stringent security treatment, we formally prove the
privacy-preserving assurance of the proposed system. To
show the generality of our system and further, expand the
scope of applications, we also demonstrate that our new
construction naturally supports fuzzy search, a notion
previously studied that aims only to tolerate types and
representation inconsistencies in theusersearchdata.The
comprehensive experiments with real data set on
Amazon's cloud platform further show the validity and
practicality of the proposed mechanism.
d. Title: Practical and efficient key word based search over
cloud data
Author: C. Orencik, M. Kantarcioglu, and E. Savas
Year: 2013
Description: Cloud computing solutions are becoming
increasingly popular each year, asmanycompaniestendto
outsource their data using reliable and efficient cloud
infrastructure, thus reducing hardware ownership costs.
Even though the benefits are welcomed, privacy remains a
problem awaiting addressing. We are implementing an
effective privacy conserving search method whereby uses
min hash functions over encrypted cloud data. Most
literature work can support only one feature search in
queries which reduces performance. One of the main
benefits ofourproposedapproachismulti-keywordsearch
functionality in a single query. The proposed method is
proven to fulfill the concept of adaptive mean time
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 07 Issue: 04 | Apr 2020 www.irjet.net p-ISSN: 2395-0072
© 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 267
protection. We also incorporate an efficient ranking
capability that is based on thevalues ofkeyworddocument
pairs in the term frequency-inverse document frequency
(TF-IDF). Our research shows that the proposed schemeis
known to be reliable, efficient and successful in protecting
privacy.
e.Title: Idea conceptual resemblance the methodology
focused on generative grammar and concepts
characteristics constitution
Author: M. Li, B. Lang, and J. Wang
Year: 2015
Description: In information retrieval, knowledge
acquisition and many other fields, calculation of
memantine similarity between words are important. The
latest studies aim primarily at single definitions consisting
of single words. They typically ignore the unique
constitutional characteristics of compounds for the
compound concepts composed of multiple terms and only
process them as single concepts, which can affect the
ultimate accuracy. In this paper, we propose a novel
ontology-based method for the measurement of the
Compound Concept Semantic Similarity called CCSS that
exploits the features of the concept constitution. The
composite is decomposed into Subject headings and
Auxiliary Words (SAA) in CCSS and the connections
between such two sets are used to calculate the similarity.
Additionally, the defects that can arise from SAA
recognition are corrected. In addition, many ontological
sources of knowledge such as taxonomic characteristics,
regional density, and depth are regarded. Extensive
experimental evaluations show that our approach greatly
outperforms current approaches.
4. EXISTING SYSTEM
Keyword-based information retrieval, commonly used for
searching from cloud storage on plaintext data. The data
encryption is a standard way of raising information
leakage. However, this will make it a very difficult job to
use data on the server-side, such as looking for encrypted
data. Researchers have suggested several cipher text
search schemes in recent years, by integrating the
techniques of cryptography. Such methods require large
operations and are very time-complex. Keyword Guessing
Attack is going to happen in this program, the hackers can
easily guess the keyword because they can easily hack our
content from the cloud server. The current search method
can only have the result based on the Boolean keyword
matching scheme, meaning that the actual name of the file
would be the same as the keyword that the file would be
retrieved from the server, and no search results would be
given for misspelled keywords. And the current search
system still never delivers the result based on related
keywords. Multi keyword search and fuzzy search were
introduced separately, and a combination of the two will
not result in a stable and efficient multi-keyword fuzzy
search scheme. Fuzzy multi-keyword search over
encrypted user data protection problem.
5. PROPOSED SYSTEM
Qualified search scheme for cloud storage information by
multi-keyword. Here we use the nebulous keyword
collection to build the keywords that are all feasible for
misspelling. Search keyword get encryptedandtestthefile
name in the cloud server with the original encrypted
collection if the keyword matches then we link the
nebulous keyword set for that particular keyword and
search the file list based on the nebulous keywords,
recover the files from the cloud server and find the search
output here as well. Extensivepreliminaryfindingsonreal-
life data sets demonstrate that our proposed solution can
greatly boost the ability to protect privacy infringements,
the scalability and the time-efficiency of query processing
over state-of - the-art methods. The keyword control
frequencies are taken into consideration when the
program produces a graded return results list. The data
owner should monitor the ability to unlink Query rates
without losingaccuracyandbetter-protectingdata privacy.
6. MODULES
a. Login/New User: Within this section, there is a lot of
protection to the login construction itself. Typically, the
name of the user account and the correct password of that
account are sufficient to explain and login, but here are
some more actions to do more.
b. Upload File: We want to load the input data in this
module then read the input data file and apply the pre-
processing to that input file. And the attached file can be
transferred into the next steps.
c. Frequent search: This module, we get the non-stop
words as input and measure the number of words andfind
repeated occurrence from non-stop words of each and
every word.
d. Similarity search: From the maximum frequency word
we find the weight age of each and every word to measure
the similarity between the terms based on the similarity
that we will divide the terms into clusters.
e. Linear search: In this module we will create keyword
search, each cluster has n number of similar terms as
keywords we will find the file for that cluster using the
lexical analysis tool.
f. Mail alert process: The user's upload and update
process must first get the secret key in the relevant user
email I d and then apply the secret key to encrypteddata to
send the server storage and decrypt it using the secret key
to access the corresponding data file to the private key
conversion of the server storage solutionusingtheSharing
KeyGen (SKA, t, m)..
g. File Downloading process: The method of uploading
files is to get the corresponding secret key to the
corresponding file to the user mail I d and decrypt the file
data afterward. The decryption key for the file transfer
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 07 Issue: 04 | Apr 2020 www.irjet.net p-ISSN: 2395-0072
© 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 268
process to storage servers, so that storageserversperform
the decryption procedure. And download the file.
7. ARCHITECTURE DIAGRAM
Fig-1: Architecture diagram
8. OUTPUT SCREENSHOTS
Fig-2: Main page
Fig-3: Admin login
Fig-4: File upload
Fig-5: Search page
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 07 Issue: 04 | Apr 2020 www.irjet.net p-ISSN: 2395-0072
© 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 269
Fig-6: Download file
9. FUTURE ENHANCEMENT
It maintains the confidentiality and security of the files
stored in the cloud and this keyword-based search helps
preserve the above. This can be achieved in a differentway
to incorporate more functionality at every part of the
device to improve the system's security and health.
10. CONCLUSION
A protected multi-keyword search scheme ranked above-
encrypted cloud data which simultaneously facilitates
dynamic update operations suchas removal anddocument
insertion. The cloud server runs through differentpathson
the index and the data user expects different results but
with the same high degree of query accuracy whilst. The
keyword-based search is also one commonly used data
operator in many applications for database and
information retrieval, and its conventional processing
methods cannot be applied directly to encrypted data. So
how to process these requests over encrypted data while
maintaining data privacy at the same time. Then we build
the multi-keywordtop-k searchschemeto boostthesearch
performance, which divides the dictionary into multiple
groups and only needs to be stored In the sense that you
don't need to send the exact filename to download the file,
if you send the maximum number of repeated terms, that
time will be downloaded in the decryptedformataswell as
the original file. This helps keep the files in the cloud
secure.
REFERENCES
[1] D. X. Song, D. Wagner, and A. Perrig, “Practical
techniques for searches on encrypted data,” in
IEEE Symposium on Security and Privacy, 2000,
pp. 44–55.
[2] B. Wang, S. Yu, W. Lou, and Y. T. Hou, “Privacy-
preserving multi-keyword fuzzy search over
encrypted data in the cloud,” inIEEEInternational
Conference on Computer Communications, 2014,
pp. 2112–2120.
[3] M. Kuzu, M. S. Islam, and M. Kantarcioglu,
“Efficient similarity search over encrypted data,”
in IEEE 28th International Conference on Data
Engineering (ICDE), 2012, pp. 1156–1167.
[4] C. Wang, K. Ren, S. Yu, and K. M. R. Urs, “Achieving
usable and privacy-assured similaritysearchover
outsourced cloud data,” in 2012 Proceedings of
IEEE INFOCOM, 2012, pp. 451–459.
[5] C. Orencik, M. Kantarcioglu, and E. Savas, “A
practical and secure multi-keyword search
method over encrypted cloud data,” in IEEE Sixth
International Conference on Cloud Computing
(CLOUD), 2013, pp. 390–397.
[6] M. Li, B. Lang, and J. Wang, “Compound concept
semantic similarity calculation based on ontology
and concept constitution features,” in Tools with
Artificial Intelligence (ICTAI), 2015 IEEE 27th
International Conference on, 2015, pp. 226–233.
[7] Z. Zhou, Y. Wang, and J. Gu, “A new model of
information content for semantic similarity in
wordnet,” in Future Generation Communication
and Networking Symposia, 2008. FGCNS’08.
Second International Conference on, vol. 3. IEEE,
2008, pp. 85–89.
[8] H. Hu, J. Xu, C. Ren, and B. Choi, “Processing
private queries over untrusteddata cloudthrough
privacy homomorphism,” in 2011 IEEE 27th
International Conference on Data Engineering,
2011, pp. 601–612.
[9] Z. Fu, X. Sun, N. Linge, and L. Zhou, “Achieving
Effective Cloud Search Services: Multi-keyword
Ranked Search over Encrypted Cloud Data
Supporting Synonym Query,” IEEE Transaction
Consumer Electronics, vol. 60, no.1, pp. 164-172,
2014.
[10] Q. Chai and G. Gong, “Verifiable Symmetric
Searchable Encryption for Semi- Honest-but-
Curious Cloud Servers,” IEEE International
Conference on Communications (ICC’12),pp.917-
922, 2012.

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IRJET - K-Gram based Composite Secret Sign Search Over Encrypted Cloud Information

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 04 | Apr 2020 www.irjet.net p-ISSN: 2395-0072 © 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 265 K-Gram based Composite Secret Sign Search over Encrypted Cloud Information Aditi Gaur1, Y.Geetha Sai2, Shriya G.N3 1,2,3Student, Dept. of Computer Science and Engineering, SRM Institute of Science and Technology, Tamil Nadu, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - A growing number of owners of data has transferred our data to cloud servers. Cloud data owners tend to outsource information in an encrypted form for confidentiality protection purposes. Developing an effective and reliable search method for cipher-text is therefore important. One problem is that the relationship between documents is usually hidden in theencryptionprocess, which can lead to a substantial deterioration oftheefficiencyofthe search accuracy. Using the keyword-based app, all access data from the cloud. The stable multi-keyword ranked cloud to search for encrypted data, a top-k quest for big data encryption against breaches of privacy, and attempt to find an efficient and safe solution to this problem. It provides open operations such as downloading, removing, adding information. Using tree structure and nebulous search method here to retrieve the cloud data. These types of techniques are used to solve the keyword conjecture attack problem. This offers transparent operations suchascopying, deleting, and information adding. The cloud data is extracted using a tree structureandnebuloussearchmethod here. These types of strategies are used to solve the problem of attack by keyword conjecture. Key Words: Cloud computing, Multi keyword search, Java, Semantic resemblance, Encryption 1. INTRODUCTION Cloud computing infrastructure is ground-breaking new technology and it significantly accelerates the production of data storage, processing, and delivery on a wide scale. Nevertheless, as data owners outsource their private data to public cloud providers that are not within their trusted management jurisdictions, security and privacy become major concerns. To avoid leakage of information, sensitive data must be encrypted. Most existing works find only queries of single keywords without sufficient ranking schemes. The keyword dictionary is static withthecurrent multi-graded search strategy, and cannot be easily expanded as the number of keywords grows. It also takes no account of the user behaviour and the frequency of keyword access. The out-of-order therankingproblemcan emerge for the query matching result which contains a large number of documents. This makes it difficult for the data used to find the subset which most likely meets their requirements. In this paper, we propose a versatile multi- keyword query scheme, called MKQE to resolve the above disadvantages. MKQE significantly decreasestheoverhead management during the extension of the dictionary keyword. When generating the query result it takes into account keyword weights and user access history. Hence, records that have higher levels of access and that fit more to the access history of the users get higher rankings in the corresponding result collection. Thepurposeoftheproject is to provide users with various types of search options to get the full number of file searches from the cloud's encrypted data. 2. RELATED WORK Using fuzzy search algorithms to upload the file we can create lots of keywords for each file hereby providing the statics based on different conditions, we can highlight the output report of all these enhancedsearchmechanisms.By providing the statics dependent on various circumstances, we can highlight the output report of all such enhanced search mechanisms. Keyword Guessing Attack is going to happen in this program, the hackers can easily guess the keyword because they can easilyhack ourcontentfromthe cloud server. The current search method can only provide the result based on the matching framework for Boolean keywords, meaning that the environment would consider the exact file name exactly the same as the keyword that the file would be retrieved from the server, it will not have any search results for misspelled keywords. And the new search system never produces results based on related keywords. Using fuzzy search algorithms to upload the file we can create lots of keywords for each file hereby providing the statics based on a differentcondition,wecan highlight the output report of all these enhanced search mechanisms. By providing the statics dependent on various circumstances, we can highlight the output report of all such enhanced search mechanisms. 3. LITERATURE SURVEY a. Title: Practical technological searches on encrypted data Author: D. X. Song, D. Wagner, and A. Perrig Year: 2000 Description: To that the protection and privacy risks, it is beneficial to store data on data storage servers such as mail servers and file servers in encryptedform.Ciphertext;
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 04 | Apr 2020 www.irjet.net p-ISSN: 2395-0072 © 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 266 provide isolation of the search query, meaning that the untrusted server can't know more about theplaintextthan the search result; provide controlled search so that the untrusted server can learn something more about the plaintext. The algorithms we present are simple, fast (the encryption and searchalgorithmsonlyrequireO(n)stream cipher and block cipher operations for a document of length n), and add almost no overhead space and communication and are therefore practical to use nowadays. Yet this typically means one hastocompromise protection features. For example, if a client needs only documents containing those terms to be retrieved, it was not previously understood how to allow the data storage server to conduct the search and address the question without sacrificing data confidentiality. Within this paper, we define our cryptographic schemes for the search problem on encrypted data and providesecurity proofsfor the resulting cryptosystems. There are a number of important they are known to be secure: they provide known confidentiality for encryption, in the sense that the untrusted server cannot learn more about the plaintext when only provided. b. Title: privacy synonym based fuzzy multi keyword graded search over encrypted cloud Author: B.Wang, S.Yu, W. Lou, and Y. T. Hou Year: 2014 Description: Cloud Storage is one of the most commonly used cloud technologies at this time. As cloud use increases, sensitive and personal data are also outsourced which makes it necessary to protecttheconfidentialityand integrity of this data. A simple way to secure data is to encrypt it before outsourcing, but the recovery of the necessary files from the encrypted cloud becomes a problem involving searching through the encrypted data. Different schemes have been proposed to fix this issue of searching over encrypted cloud data, but none of the current schemes offer ideal user search experience that Plaintext search. In this paper, we suggest privacy search meaning Fuzzy Multi-Keyword Ranked Search over Encrypted Cloud Data, a plan of action that enhances the user search experience to the greatest level by offering multi-keyword searches based on both fuzzy and synonymous, thus bringing encrypted search experience closer to free search engines for text.Inaddition,byusinga binary tree-based dynamic index, the scheme increases index generation time and search the time relative to existing schemes. Experimental findings reflect the effectiveness of this proposed scheme as it decreases the search time, i.e. the time to locate the required data, by 90 percent and minimizes the overhead of database updates when new files need to be uploaded (database generation time)Compared with current effective indexing schemes for similar datasets in the literature. To this point, search time optimization along with index generation time was not done before. c.Title: Similarity over outsourced cloud data achieving used and privacy secured Author: C.Wang, K. Ren, S. Yu, and K. M. R. Urs Year: 2012 Description: As the data generated by individuals and companies needing to be processed and used is growing rapidly, data owners are encouraged to outsource their complex local data management systems to the cloud for their tremendous versatility and economical savings. Nevertheless, because sensitive cloud data that need to be encrypted before outsourcing, which obsolescence the conventional data management service basedonplaintext keyword search, how privacy-assured usage mechanisms for outsourced cloud data are therefore of paramount importance. Considering the vast number of on-demand data users and the massive volume of outsourceddata files in the cloud, the issue is especially daunting because it is incredibly difficult to satisfy the realistic performance criteria, device accessibility, andusersearchexperiences at the highest level. In this paper, we discuss the question of searching for stable and efficient similarity over outsourced cloud data. Similarity search is a fundamental and powerful method commonly used in the retrieval of plaintext content, but not quite explored in the encrypted data domain. First, our mechanism architecture takes advantage of a suppressing technique to create storage- efficient keyword similarity from a given document set, editing distance as the similarity metric. We then create a private tire-traverse search index based on that, and display it correctly achieves the given search similarity functionality with constant search time complexity. Under stringent security treatment, we formally prove the privacy-preserving assurance of the proposed system. To show the generality of our system and further, expand the scope of applications, we also demonstrate that our new construction naturally supports fuzzy search, a notion previously studied that aims only to tolerate types and representation inconsistencies in theusersearchdata.The comprehensive experiments with real data set on Amazon's cloud platform further show the validity and practicality of the proposed mechanism. d. Title: Practical and efficient key word based search over cloud data Author: C. Orencik, M. Kantarcioglu, and E. Savas Year: 2013 Description: Cloud computing solutions are becoming increasingly popular each year, asmanycompaniestendto outsource their data using reliable and efficient cloud infrastructure, thus reducing hardware ownership costs. Even though the benefits are welcomed, privacy remains a problem awaiting addressing. We are implementing an effective privacy conserving search method whereby uses min hash functions over encrypted cloud data. Most literature work can support only one feature search in queries which reduces performance. One of the main benefits ofourproposedapproachismulti-keywordsearch functionality in a single query. The proposed method is proven to fulfill the concept of adaptive mean time
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 04 | Apr 2020 www.irjet.net p-ISSN: 2395-0072 © 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 267 protection. We also incorporate an efficient ranking capability that is based on thevalues ofkeyworddocument pairs in the term frequency-inverse document frequency (TF-IDF). Our research shows that the proposed schemeis known to be reliable, efficient and successful in protecting privacy. e.Title: Idea conceptual resemblance the methodology focused on generative grammar and concepts characteristics constitution Author: M. Li, B. Lang, and J. Wang Year: 2015 Description: In information retrieval, knowledge acquisition and many other fields, calculation of memantine similarity between words are important. The latest studies aim primarily at single definitions consisting of single words. They typically ignore the unique constitutional characteristics of compounds for the compound concepts composed of multiple terms and only process them as single concepts, which can affect the ultimate accuracy. In this paper, we propose a novel ontology-based method for the measurement of the Compound Concept Semantic Similarity called CCSS that exploits the features of the concept constitution. The composite is decomposed into Subject headings and Auxiliary Words (SAA) in CCSS and the connections between such two sets are used to calculate the similarity. Additionally, the defects that can arise from SAA recognition are corrected. In addition, many ontological sources of knowledge such as taxonomic characteristics, regional density, and depth are regarded. Extensive experimental evaluations show that our approach greatly outperforms current approaches. 4. EXISTING SYSTEM Keyword-based information retrieval, commonly used for searching from cloud storage on plaintext data. The data encryption is a standard way of raising information leakage. However, this will make it a very difficult job to use data on the server-side, such as looking for encrypted data. Researchers have suggested several cipher text search schemes in recent years, by integrating the techniques of cryptography. Such methods require large operations and are very time-complex. Keyword Guessing Attack is going to happen in this program, the hackers can easily guess the keyword because they can easily hack our content from the cloud server. The current search method can only have the result based on the Boolean keyword matching scheme, meaning that the actual name of the file would be the same as the keyword that the file would be retrieved from the server, and no search results would be given for misspelled keywords. And the current search system still never delivers the result based on related keywords. Multi keyword search and fuzzy search were introduced separately, and a combination of the two will not result in a stable and efficient multi-keyword fuzzy search scheme. Fuzzy multi-keyword search over encrypted user data protection problem. 5. PROPOSED SYSTEM Qualified search scheme for cloud storage information by multi-keyword. Here we use the nebulous keyword collection to build the keywords that are all feasible for misspelling. Search keyword get encryptedandtestthefile name in the cloud server with the original encrypted collection if the keyword matches then we link the nebulous keyword set for that particular keyword and search the file list based on the nebulous keywords, recover the files from the cloud server and find the search output here as well. Extensivepreliminaryfindingsonreal- life data sets demonstrate that our proposed solution can greatly boost the ability to protect privacy infringements, the scalability and the time-efficiency of query processing over state-of - the-art methods. The keyword control frequencies are taken into consideration when the program produces a graded return results list. The data owner should monitor the ability to unlink Query rates without losingaccuracyandbetter-protectingdata privacy. 6. MODULES a. Login/New User: Within this section, there is a lot of protection to the login construction itself. Typically, the name of the user account and the correct password of that account are sufficient to explain and login, but here are some more actions to do more. b. Upload File: We want to load the input data in this module then read the input data file and apply the pre- processing to that input file. And the attached file can be transferred into the next steps. c. Frequent search: This module, we get the non-stop words as input and measure the number of words andfind repeated occurrence from non-stop words of each and every word. d. Similarity search: From the maximum frequency word we find the weight age of each and every word to measure the similarity between the terms based on the similarity that we will divide the terms into clusters. e. Linear search: In this module we will create keyword search, each cluster has n number of similar terms as keywords we will find the file for that cluster using the lexical analysis tool. f. Mail alert process: The user's upload and update process must first get the secret key in the relevant user email I d and then apply the secret key to encrypteddata to send the server storage and decrypt it using the secret key to access the corresponding data file to the private key conversion of the server storage solutionusingtheSharing KeyGen (SKA, t, m).. g. File Downloading process: The method of uploading files is to get the corresponding secret key to the corresponding file to the user mail I d and decrypt the file data afterward. The decryption key for the file transfer
  • 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 04 | Apr 2020 www.irjet.net p-ISSN: 2395-0072 © 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 268 process to storage servers, so that storageserversperform the decryption procedure. And download the file. 7. ARCHITECTURE DIAGRAM Fig-1: Architecture diagram 8. OUTPUT SCREENSHOTS Fig-2: Main page Fig-3: Admin login Fig-4: File upload Fig-5: Search page
  • 5. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 04 | Apr 2020 www.irjet.net p-ISSN: 2395-0072 © 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 269 Fig-6: Download file 9. FUTURE ENHANCEMENT It maintains the confidentiality and security of the files stored in the cloud and this keyword-based search helps preserve the above. This can be achieved in a differentway to incorporate more functionality at every part of the device to improve the system's security and health. 10. CONCLUSION A protected multi-keyword search scheme ranked above- encrypted cloud data which simultaneously facilitates dynamic update operations suchas removal anddocument insertion. The cloud server runs through differentpathson the index and the data user expects different results but with the same high degree of query accuracy whilst. The keyword-based search is also one commonly used data operator in many applications for database and information retrieval, and its conventional processing methods cannot be applied directly to encrypted data. So how to process these requests over encrypted data while maintaining data privacy at the same time. Then we build the multi-keywordtop-k searchschemeto boostthesearch performance, which divides the dictionary into multiple groups and only needs to be stored In the sense that you don't need to send the exact filename to download the file, if you send the maximum number of repeated terms, that time will be downloaded in the decryptedformataswell as the original file. This helps keep the files in the cloud secure. REFERENCES [1] D. X. Song, D. Wagner, and A. Perrig, “Practical techniques for searches on encrypted data,” in IEEE Symposium on Security and Privacy, 2000, pp. 44–55. [2] B. Wang, S. Yu, W. Lou, and Y. T. Hou, “Privacy- preserving multi-keyword fuzzy search over encrypted data in the cloud,” inIEEEInternational Conference on Computer Communications, 2014, pp. 2112–2120. [3] M. Kuzu, M. S. Islam, and M. Kantarcioglu, “Efficient similarity search over encrypted data,” in IEEE 28th International Conference on Data Engineering (ICDE), 2012, pp. 1156–1167. [4] C. Wang, K. Ren, S. Yu, and K. M. R. Urs, “Achieving usable and privacy-assured similaritysearchover outsourced cloud data,” in 2012 Proceedings of IEEE INFOCOM, 2012, pp. 451–459. [5] C. Orencik, M. Kantarcioglu, and E. Savas, “A practical and secure multi-keyword search method over encrypted cloud data,” in IEEE Sixth International Conference on Cloud Computing (CLOUD), 2013, pp. 390–397. [6] M. Li, B. Lang, and J. Wang, “Compound concept semantic similarity calculation based on ontology and concept constitution features,” in Tools with Artificial Intelligence (ICTAI), 2015 IEEE 27th International Conference on, 2015, pp. 226–233. [7] Z. Zhou, Y. Wang, and J. Gu, “A new model of information content for semantic similarity in wordnet,” in Future Generation Communication and Networking Symposia, 2008. FGCNS’08. Second International Conference on, vol. 3. IEEE, 2008, pp. 85–89. [8] H. Hu, J. Xu, C. Ren, and B. Choi, “Processing private queries over untrusteddata cloudthrough privacy homomorphism,” in 2011 IEEE 27th International Conference on Data Engineering, 2011, pp. 601–612. [9] Z. Fu, X. Sun, N. Linge, and L. Zhou, “Achieving Effective Cloud Search Services: Multi-keyword Ranked Search over Encrypted Cloud Data Supporting Synonym Query,” IEEE Transaction Consumer Electronics, vol. 60, no.1, pp. 164-172, 2014. [10] Q. Chai and G. Gong, “Verifiable Symmetric Searchable Encryption for Semi- Honest-but- Curious Cloud Servers,” IEEE International Conference on Communications (ICC’12),pp.917- 922, 2012.