Scalable and Efficient Provable Data
Possession in Multi cloud Environment
Ms.Manasa.P1, Mrs.Vanishree Abhay2
1
(M.Tech-CNE, Department of Information Science & Engineering, Dr.AIT, Bengaluru)
2 (Assistant Professor, Department of Information Science & Engineering, Dr.AIT, Bengaluru)
ABSTRACT: Cloud computing is rapidly
consist group of clouds. Internal attacker problem
developing new technology for the complex system
and security problem are major problem in multi
with massive scale sharing among numerous users.
cloud environment. For secure communication,
Authentication of user and service are significant
reliability, authentication is important in multi
issues for the trust and security of the Cloud
cloud environment. Authentication is checked and
Computing. Remote data integrity checking is very
verified in each operation of the task. Different
important in cloud storage. Client can verify his
clouds combination is multi cloud environment.
data without downloading whole data based on
application. The clients have to store their data on
Main Objectives of Multi cloud storage
Multi Cloud Server. Integrity checking protocol is
Security: Data and Information will be shared with
used while storing data in Multi Cloud Server and
external users, therefore cloud computing users
it must be efficient to save the clients data. This
want to avoid important information from attackers
implementation paper proposes efficient method
or malicious insider is of critical importance. Three
for remote data integrity checking model called
factors are:
Identity
Based
Distributed
Provable
Data
Possession (ID-DPDP) in Multi Cloud storage. The
ID-DPDP protocol is designed based on bilinear



Data integrity
Data intrusion
Service availability
pairing and it eliminates of certificate management.
Performance:
How well multi cloud able to
KEYWORDS: Cloud Computing, Multi cloud,
handle different request and responses from
Provable Data Possession, Data Integrity Checking.
different clients simultaneously.
I.INTRODUCTION
Cost-Reduction:
Secured
storage
and
data
availability can be provided to the customers in the
Cloud computing is a new technology and can be
market of economical distribution of information in
defined as software’s can be used without having
all the available service providers.
own hardware. It is mainly used to store the
different types of information of different user’s.
Based on no. of server’s cloud computing
environment divided into Single cloud sever and
Multi cloud server. Multi cloud environment
II. RELATED WORK
In cloud computing, remote data integrity
checking is an important security problem. The
clients’ massive data is outside his control. The
malicious cloud server may corrupt the client’s data
corresponding cloud servers. When receiving the
in order to gain more benefits. Many researchers
challenge, it splits the challenge and distributes
proposed the corresponding system model and
them to the different cloud servers. When receiving
security model. In 2007, provable data possession
the responses from the cloud servers, it combines
(PDP) paradigm was proposed. Provable data
them and sends the combined response to the
possession (PDP) protocol [1]l, it needs public key
verifier.
certificate distribution and management. This
4) PKG (Private Key Generator): an entity, when
protocol will reduce overheads when it checks the
receiving the identity, it outputs the corresponding
remote data integrity, verifiers will check the
private key.
certificate. Provable Data Possession method
reduces the overhead on client by without
downloading whole content. The system suffers
from the complicated certificates management such
as certificates generation, revocation, delivery, etc.
In cloud computing, most verifiers attain low
computation capacity. Here Low computation due
to overhead on each cloud server. Public key
cryptography
can
eliminate
the
complicated
Figure 1: ID-DPDP Architecture
certificate management. In order to increase the
efficiency, this project, Scalable and Efficient
This protocol comprises four procedures: Setup,
provable data possession is more effective.
Extract, TagGen, and Proof. The fig.3 can be
described as follows: 1. In the phase Extract, PKG
III. PROTOCOL ANALYSIS
The
ID-DPDP
system
model
and
security
definition are presented in this section. An IDDPDP [2] protocol comprises four different entities
which are illustrated in Fig 1. Described as below:
creates the private key for the client.2. The client
creates the block-tag pair and uploads it to
combiner. The combiner distributes the block-tag
pairs to the different cloud servers according to the
storage metadata. 3. The verifier sends the
challenge to combiner and the combiner distributes
1) Client: an entity, which has massive data to be
stored on the multi-cloud for maintenance and
computation, can be either individual consumer or
corporation.
the challenge query to the corresponding cloud
servers according to the storage metadata. 4. The
cloud servers respond the challenge and the
combiner aggregates these responses from the
cloud servers. The combiner sends the aggregated
2) CS (Cloud Server): an entity, which is managed
response to the verifier. Finally, the verifier checks
by cloud service provider, has significant storage
whether the aggregated response is valid. The
space and computation resource to maintain the
concrete ID-DPDP construction mainly comes
clients’ data.
from the signature, provable data possession [4]
and distributed computing. The signature relates
3) Combiner: an entity, which receives the storage
the
client’s
identity
with
his
private
key.
request and distributes the block-tag pairs to the
Distributed computing is used to store the client’s
data on multi-cloud servers. At the same time,
(blocks) of their interest from the cloud
distributed computing is also used to combine the
Servers and then combines them in
multi-cloud servers’ responses to respond the
Combiner. The CS can modify the
verifier’s challenge. Based on the provable data
contents in the CS files in respective
possession protocol, the ID-DPDP protocol [3] is
clouds and it can regenerate by Data
constructed by making use of the signature and
Owner using the Public Verifier.
distributed computing.

Public Verifier is very important in meta
IV. IMPLEMENTATION
data information’s and verify the files in
Implemented Modules [5]

the cloud servers to maintain the data
Data Owner
integrity in particular and Data Integrity
In this module, the data owner creates the
ensured that data is of high quality,
End User and provides the auto generates
correct, consistent and accessible.
the password and uploads their data in the
cloud server. The Data
owner can

regenerate the attacked file in the cloud
Private Key Generator(PKG)
The Private Key Generator is responsible
server; the data owner can delete the file
to generate the unique key/hash key for
in the Server and have capable of
the files stores as blocks in CS (CS1, CS2,
manipulating the encrypted data file.

Public Verifier
CS3,
CS4
and
CS5).
While
its
downloading by End User the key
Combiner- Divider
generator is responsible authenticate and
The Divider is responsible to divide the
verify the key of the file and The Key
files into blocks while uploading the file
generator is authorize to check the Wright
to Cloud Server, Combiner is responsible
of the key ,If he gives the wrong key then
to combine the blocks of file and provide
it been considered as the attacker or
to the End User while he request the file to
malicious user over the cloud data.
download and get the key for the blocks.


Cloud Server
Data Consumer(End User / Group
Member)
The cloud service provider has significant
In this module, the user can only access
storage space and computation resource to
the data file with the encrypted key of
maintain the clients’ data. The cloud
different blocks, if the user has the Wright
service provider manages clouds (CS1,
key privilege to access the file. For the
CS2, CS3, CS4 and CS5) to provide data
user level, all the Hash keys are
storage service. Divider divides and gets
the KG authority and the blocks are
the Hash key for their blocks data files and
combined by the Combiner only. Users
stores them in the clouds CS1, CS2, CS3,
may try to access data files either within
CS4 and CS5) for sharing with data
or outside the scope of their access
consumers. To access the shared data files,
privileges, so malicious users may collude
a data consumer downloads data files
given by

with each other to get sensitive files
performance of the ID-DPDP proves, it is best
beyond their privileges.
secure protocol for multi cloud environment.
Energy
Utilization
during
Upload/
Download of File
In this module, a graph is generated during
V. REFERENCES
upload of a file to server and download of
file from the server. Here x-axis represents
the energy level and y-axis represents total
energy level in terms of joules. If the file
size is large it consumes more energy for
upload and download.

Time
Utilization
In this module, a graph is generated for
time delay. It represents time taken to
upload a file and download a file. Based
on size of the file, delay varies from one
file to another. Here x- axis and y-axis
download
time
delays
in
milliseconds.
V. COCLUSION
The Multi Cloud Environment is clouds of cloud.
The main issue in group of clouds is identifying the
internal attackers. The file maintenance access will
be
blocked
due
to
internal
[2] G. Ateniese, R. Burns, R. Curtmola, J. Herring,
L. Kissner, Z. Peterson,D. Song, “Provable Data
Possession at Untrusted Stores”, CCS’07, pp.598609, 2007.
during
Upload/Download of File
represents
[1] G. Ateniese, R. DiPietro, L. V. Mancini, G.
Tsudik, “Scalable and Efficient Provable Data
Possession”, SecureComm 2008, 2008.
attackers.
The
maintenance of remote data in Cloud Storage is a
difficult task. This paper implements the ID-DPDP
system model and security model for multi-cloud
storage environment. We propose the ID-DPDP
protocol which is provably secure under several
considerations. The proposed method eliminates
certificate management, efficient and flexible in
Multi Cloud environment. The ID-DPDP protocol
method easily identifies internal attackers. The files
are blocked immediately to stop the further
communication. Theoretically and practically the
[3] C. C. Erway, A. Kupcu, C. Papamanthou, R.
Tamassia, “Dynamic Provable Data Possession”,
CCS’09, pp. 213-222, 2009.
[4] H.Q. Wang, “Proxy Provable Data Possession
in PublicClouds,” IEEE Transactions on Services
Computing, 2012.
[5] A.Keerthana ,S JayaPrakash ,” Scalable
Identity-Based
Distributed
Provable
Data
Possession in Multi-Cloud Storage”, IJCSECInternational Journal of Computer Science and
Engineering Communications. Vol.3, Issue 2,
2015, Page.889-892, ISSN: 2347–8586.