International Journal of Engineering Trends and Technology (IJETT) – Volume 29 Number 7 - November 2015
Provide Security of Ranked Multi keyword Search over
Encrypted Data in cloud computing
Dharmapu Mohan Rao1, Mula.Sudhakar2
Final M.Tech Student1, Asst.professo2
Dept of CSE, Sarada Institute of Science, Technology And Management (SISTAM),
Srikakulam, Andhra Pradesh,India
1,2
Abstract: Now a day’s mobile cloud computing is
rapidly growth for searching outsource the mobile
data to external cloud servers for scalable data
storage. So that to provide security of that data is
most important issue in the cloud computing. Before
store the data into cloud the data owner will encrypt
the data using cryptography technique. After
encryption of data the data owner will stored into
cloud. If any user performing searching for retrieve
related content from the cloud he/she decrypt and
retrieve the related content. In this paper contain
mainly two concepts for privacy of data and ranked
multi keyword for search over encrypted data. To
provide privacy of data we are using segment
encryption algorithm and provide ranking of multi
keywords distinct nearest neighbor optimal
algorithm. By implementing those concepts we
improve efficiency and more security of data.
Keywords: Cloud infrastructure, Out-sourced data
security, and Multi-Keyword Search.
Data encryption process makes data
utilization a very complex and challenging task as
there could be a huge amount of outsourced data
files. Along with this, Cloud data owners may need
to share their outsourced data among large set of
users, who might want to restrict certain data files
that they want to access during a specific session.
One of the best ways to implement this is using
keyword-based
searchThis
keyword
search
technique allows users to selectively retrieve files of
interest and has been widely applied in plaintext
search scenarios. Unfortunately, data encryption,
which restricts user‟s ability to perform keyword
search and further demands the protection of
keyword privacy, makes the traditional plaintext
search methods fail for encrypted cloud data.
Ranked search greatly improves system usability by
normal matching files in a ranked order regarding to
certain relevance criteria (e.g., keyword frequency).
I. INTRODUCTION
Cloud computing is a model for enabling trending,
convenient, on-demand infrastructurewith a shared
pool of configurable computing resources like
networks,servers,
applications,storage,
and
services.These resources can be easily provisioned at
rapid speed and also can be released with least
management effort or service provider interaction.
Moreover, Cloud Computing means a remote
resource that is accessible through the internet and
helps in business applications and their functionality
along with the computer software. Cloud computing
can cut down money that users need to spend on
subscription charges. Because of these advantage of
cloud servicesa large sensitive information is being
pushed into the cloud servers, like emails, personal
health records, and also private videos and photos,
financial data, administration documents, etc. To
secure data privacy, all these confidential data need
to be encrypted prior to outsourcing, so that end-toend data confidentiality is assured in the cloud.
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Organizations, companies store more and
more valuable information is on cloud to protect
their data from virus, hacking. The benefits of the
new computing model include but are not limited to:
relief of the trouble for storage administration, data
access, and avoidance of high expenditure on
hardware mechanism, software, etc. Ranked search
improves system usability by normal matching files
in a ranked order regarding to certain relevance
criteria (e.g., keyword frequency),As directly
outsourcing relevance scores will drip a lot of
sensitive information against the keyword privacy,
we proposed asymmetric encryption with ranking
result of queried data which will give only expected
data.
So that to provide security of that data is
most important issue in the cloud computing. Before
store the data into cloud the data owner will encrypt
the data using cryptography technique. After
encryption of data the data owner will stored into
cloud. If any user performing searching for retrieve
related content from the cloud he/she decrypt and
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International Journal of Engineering Trends and Technology (IJETT) – Volume 29 Number 7 - November 2015
retrieve the related content. In this paper contain
mainly two concepts for privacy of data and ranked
multi keyword for search over encrypted data. To
provide privacy of data we are using segment
encryption algorithm and provide ranking of multi
keywords distinct nearest neighbor optimal
algorithm. By implementing that concept, we
improve efficiency and more security of data.
II. RELATED WORK
A collection of analysis works has recently been
developed on the subject of multi-keyword search
over encrypted information. Cash et al. [10] propose
a powerful searchable encoding theme that achieves
high potency for big databases with modest
scarification on security guarantees. Cao et al. [11]
propose a multi-keyword search theme sup- porting
result ranking by adopting k-nearest neighbors (kNN)
technique [12]. Naveed et.al. [13] propose a dynamic
search- ready encoding theme through blind storage
to hide access pattern of the search user.
In order to satisfy the sensible search necessities,
search over encrypted information ought to support
the subsequent 3 functions. First, the searchable
encoding schemes ought to support multi-keyword
search, and supply constant user expertise as looking
out in Google search with completely different
keywords; single-keyword search is much from
satisfactory by solely returning terribly restricted and
inaccurate search results. Second, to quickly
establish most relevant results, the search user would
generally like cloud servers to type the came search
leads to a relevancy-based order [14] graded by the
relevance of the search request to the documents.
additionally, showing the graded search to users may
eliminate the unessential network traffic by solely
causing back the foremost relevant results from
cloud to go looking users. Third, as for the search
potency, since the amount of the documents
contained during a information may well be terribly
massive, searchable encoding schemes ought to be
economical to quickly answer the search requests
with minimum delays.
on security of cloud sourcing data for
theunauthorized users. So that to provide security of
cloud data the data owner will encrypt the data using
segment encryption algorithm. After encrypting the
data owner will stored data into cloud. If any user
retrieve related documents of query before decrypt
and search all plain documents. By performing
searching operation the user will get related
document of query and also ranked key words. For
the purpose of ranking keywords we are using
distinct nearest neighbor algorithm. In this paper we
are considering three different entities as illustrate in
given below figure.
Data owner:
The data owner contains collection of data
document to be send cloud server. Before sending
data to cloud server the data owner will encrypt the
data document using segment encryption algorithm.
The segment encryption algorithm is feistel type
cipher that uses operation of mixed type of algebraic
expression. In this process the data can be performed
the dual shifts of all bits and key to mixed up to
completion of all rounds. In this process mainly
depend on key schedule algorithm is a simple. In
the key schedule algorithm the k is split into four 32
bit blocks. So those segment encryption algorithms
are highly resistant of different cryptanalysis and
also improve complete diffusion. where a one bit
difference in the plaintext will cause approximately
32 bitdifferences in the cipher text.
Psedocode of encryption process:
void code(long* v, long* k)
{
long y = v[0], z = v[1], sum = 0;
delta = 0x9e3779b9, n = 32 ;
while (n-->0)
{
sum += delta ;
y += (z<<4)+k[0] ^ z+sum ^ (z>>5)+k[1] ;
z += (y<<4)+k[2] ^ y+sum ^ (y>>5)+k[3] ;
}
v[0] = y ; v[1] = z ;
}
III. PROPOSED SYSTEM
The purpose of proposed system is to choose
principles of coordinate matching and also identify
the similarity between search quires. The proposed
system also finds query related documents based on
number of key words in a query. So that the number
of times of query keyword appearing in a document
to specify the similarity that document for the query
matching principles. Here we can also concentrate
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International Journal of Engineering Trends and Technology (IJETT) – Volume 29 Number 7 - November 2015
The encryption process will take the plain
text block and key as input.The plaintext is P =
Left[0],Right[0]) and the cipher text is C = (Left[64],
Right[64]). The plaintext block is split into two
halves, Left[0] and Right[0]. Each half is used to
encrypt the other half over 64rounds of processing
and then combine to produce the cipher text block.
• Each round i has inputs Left[i-1] and Right[i-1],
derived from the previous round,
as well as a sub key K[i] derived from the 128 bit
overall K.
• The sub keys K[i] are different from K and from
each other.
• The constant delta =( 5 - 1)*231 = , is derived from
the golden h 9E3779B9
number ratio to ensure that the sub keys are distinct
and its precise value has no
cryptographic significance.
• The round function differs slightly from a classical
Fiestel cipher structure in that
integer addition modulo 2³² is used instead of
exclusive-or as the combining operator.
The round function, F, consists of the key
addition, bitwise XOR and left and right shift
operation. We can describe the output (Left[i +1] ,
Right[i +1] ) of the ith cycle of segment encryption
algorithm with the input (Left[i] ,Right[i] ) as
follows
Left [i+1] = Left[i] F ( Right[i], K [0, 1], delta[i] ),
Right [i +1] = Right[i] F ( Right[i +1], K [2, 3],
delta[i] ),
delta[i] = (i +1)/2 * delta,
The round function, F, is defined by
F(M, K[j,k], delta[i] ) = ((M << 4) K[j]) ⊕(M
delta[i] ) ⊕((M >> 5) K[k]).
The round function has the same general structure
for each round but is parameterized bythe round sub
key K[i]. The key schedule algorithm is simple; the
128-bit key K is splitinto four 32-bit blocks K =
( K[0], K[1], K[2], K[3]). The keys K[0] and K[1]
are used inthe odd rounds and the keys K[2] and K[3]
are used in even rounds.
Psedocode of decryption process:
void decode(long* v, long* k)
{
unsigned long n = 32, sum, y = v[0], z = v[1],
delta = 0x9e3779b9 ;
sum = delta<<5 ;
/ * start cycle */
while (n-->0)
{
z - = (y<<4)+k[2] ^ y+sum ^ (y>>5)+k[3] ;
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International Journal of Engineering Trends and Technology (IJETT) – Volume 29 Number 7 - November 2015
y -= (z<<4)+k[0] ^ z+sum ^ (z>>5)+k[1] ;
sum -= delta ;
}
/* end cycle */
v [0] = y ; v[1] = z ;
}
Decryption is essentially the same as the
encryption process; in the decode routine the cipher
text is used as input to the algorithm, but the sub
keys K[i] are used in the reverse order.
The intermediate value of the decryption process is
equal to the corresponding value of the encryption
process with the two halves of the value swapped.
For example, if the output of the nth encryption
round is
ELeft[i] || ERight[i] (ELeft[i] concatenated with
ERight[i]).
Then the corresponding input to the (64-i)th
decryption round is
DRight[i] || DLeft[i] (DRight[i] concatenated with
DLeft[i]).
After the last iteration of the encryption process, the
two halves of the output are swapped, so that the
cipher text is ERight[64] || ELeft[64], the output of
that round is the final cipher text C. Now this cipher
text is used as the input to the decryption algorithm.
The input to the first round is ERight[64] ||
ELeft[64], which is equal to the 32-bit swap of the
output of the 64th round of the encryption process.
After completion of encryption the data owner will
stored data into cloud services.
Cloud Service:
The cloud service will contain collection of cipher
data documents. If any user send request query to
cloud services and services will take the request send
to ranked based documents to users. To perform the
multi keyword ranked technique we are using
distinct nearest neighbor algorithm. The process of
distinct nearest neighbor algorithm as follows.
1.
2.
3.
4.
Initialize all the documents in the cloud
services.
Find the number of similar words in
document based on request query.
After find the count of each word in
document we can sort all document related
to the query.
Display the count of each word in the
document and find file relevance of each
document .
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5.
After that the ranked keyword send to user.
User:
Each user send the request query to cloud
service and service will send query similarity
document to user. The cloud service also send the
ranked words of query to user. So that by
implementing those concept we can provide more
security and efficiency of given process.
I V.CONCLUSIONS
For the purpose of proposed system is to provide
similar type of documents based on searched
keywords of the query. In this paper we are proposed
query based searching of cloud source document. By
implementing those we can rank the keyword of the
query. For the purpose we are implementing distinct
nearest neighbour algorithm for finding similar
documents of the query. Before performing
searching operation the data owner will encrypt the
document data and stored into cloud server. By
performing encryption and decryption we are using
segment based encryption algorithm. After storing
collection of documents in the server the user will
retrieve query related documents and also give the
ranking of each word in a query.
V. References
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“key encryption with keyword search”, in Proc. of
EUROCRYP‟04, volume 3027 of LNCS. Springer, 2004.
[3].Chang and Mitzenmacher, “Privacy preserving keyword
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[4].Curtmola, R., Garay J. A., R. Ostrovsky and S. Kamara,
“Searchable symmetric encryption: improved definitions and
efficient constructions”, in Proc. of ACM CCS, 2006.
[5].Caoy N, Wangz C, Ming Liy, Renz K, and Wenjing L,
“Privacy-Preserving Multi-Keyword Ranked Search over
Encrypted Cloud Data”
[6].Weifeng Su, Jiying W, and F. H. Lochovsky, Member, IEEE
“Computer Society Record Matching over Query Results from
Multiple Web Databases”
[7].Srikanth, VeereshBabu, and Narasimhulu “Combined
Keyword Search over Encrypted Cloud Data Providing Security
and Confidentiality”
[8].Singhal A, “Modern information retrieval: A brief overview”,
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BIOGRAPHIES:
DharmapuMohan Rao is
student inM.Tech(CSE) in
Sarada Institute of Science
Technology
and
Management,Srikakulam.He
has receivedhis B.Tech(CSE)
Adityainstiture of technology
and
management
,Tekkali.His
interesting areas are network
security
and
web
techonologis
Mula.Sudhakaris
workingas
aAsst.professor in Sarada
Institute
of
Science,
Technology
And
Management, Srikakulam,
Andhra Pradesh. He
received his M.Tech (SE)
from Sarada Institute of
Science, Technology And
Management, Srikakulam. JNTU Kakinada Andhra
Pradesh. His research areas include Cloud
Computing,Dataminig,Network Security.
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