An Efficient PDP Scheme for Distributed Cloud Storage

International Journal of Modern Engineering Research (IJMER)
www.ijmer.com Vol. 3, Issue. 4, Jul. - Aug. 2013 pp-2317-2319 ISSN: 2249-6645
www.ijmer.com 2317 | Page
Jimnisha Shaik1
, Syed Gulam Gouse2
1
M. Tech, Nimra College of Engineering & Technology, Vijayawada, A.P., India
2
Professor, Dept.of CSE, Nimra College of Engineering & Technology, Vijayawada, A.P., India
ABSTRACT: Cloud computing is the use of Internet for the tasks performed on the local computer, with the hardware and
software demands maintained elsewhere. It represents a different way to architect and remotely manage various computing
resources. Cloud is widely used everywhere owing to its convenience, be it in simple data analytic program or composite
web or mobile applications. Cloud computing is being driven by many which includes Amazon, Google and Yahoo as well as
traditional vendors including IBM, Microsoft and Intel. The data should be available in the cloud for it to be accessed by
many users. There are four main types of cloud storage- Multi Cloud Storage or distributed cloud storage, Public Cloud
Storage, Private Cloud Storage, Mobile Cloud Storage. Distributed cloud is a combination of public and private cloud
storage where some critical data resides in the enterprise's private cloud while other data is stored and accessible from a
public cloud storage provider. Provable data possession (PDP) is a technique for ensuring the integrity of data stored in
storage outsourcing. In this paper, we propose a method called cooperative PDP (CPDP) scheme based on homomorphic
verifiable response and hash index hierarchy.
INDEX TERMS: Cloud, Hash index, Integrity, PDP.
I. INTRODUCTION
In recent years, the concept of parallel computing has emerged to solve the problems with a greater computational
speed. It‟s operation is based upon the principle that larger problems can be reduced to a number of smaller ones, then which
are solved parallely.Parallel computing can be implemented in several ways of computing like bit level, instruction level,
task and data parallelism. Based on the level at which the hardware supports parallelism, it can be classified as- multi-core
and multi-processor. Generally in a computer system a problem can be solved using a stream of instructions. Only one
instruction is executed at a time, and then the others are executed. On the other hand in parallel computing, uses the multi-
processing elements to solve a problem. This is accomplished by breaking the problem into various independent parts so that
each processing element can execute its part of the algorithm simultaneously with others. There is another important concept
which is responsible for the effective and efficient computation of our problem is, distributed system. Using high
performance computers connected by using high speed communication links, it is possible to build a single system consisting
of multiple computers and using it as a single consolidated system.
In a distributed system, the computers are not independent but are interconnected by a high-speed network. Here are
a few requirements for a distributed system- Like reliability and security, consistency of replicated data, concurrent
transactions, and fault tolerance. The major aim of constructing the distributed system is that its behavior should be
transparent to the user. In a distributed memory architecture if we take into account each processor has its own local storage
and all the processing is done locally. All systems are interconnected using a LAN.
In any kind of computer system which involves data storage and retrieval, availability is one of the major security
issues to be concerned. Provable Data Possession (PDP) is such a technique which ensures data availability or proof of
retrievability (POR).It‟s the proof which is provided for the storage provider, in order to prove the ownership and integrity of
client‟s data without being downloading it. The proof-checking of the data without being downloading is very important,
especially when it comes to very large sized data blocks. It is necessary because it is to be ensured that the data is not deleted
or altered. PDP schemes are very useful when it comes to these kinds of issues. However, this scheme will be effective only
for single cloud storage, but not for the distributed-cloud storage environment.
II. RELATED WORK
To check the availability and integrity of the outsourced data in cloud storages, researchers have proposed two basic
approaches called Provable Data Possession (PDP) [1] and Proofs of Retrievability (POR) [2]. In [1], the authors first
proposed the PDP model for ensuring possession of files on un trusted storages and provided an RSA-based scheme for a
static case that achieves the O(1) communication cost. In order to support dynamic data operations, the authors developed a
dynamic PDP solution called Scalable PDP [3]. They proposed a lightweight PDP scheme based on cryptographic hash
function and the symmetric key encryption, but the servers can deceive the owners by using previous metadata or responses
due to the lack of the randomness in the challenges.
In [4], the authors introduced two Dynamic PDP schemes with a hash function tree to realize O(log n)
communication and computational costs for a n-block file. The basic scheme, called DPDP-I, retains the drawback of
Scalable PDP method, and in the „blockless‟ scheme, called DPDPII. In [2], the authors presented a POR scheme, which
relies largely on preprocessing steps that the client conducts before sending a file to a CSP. Several POR schemes and
models have been recently proposed including in [5][6]. In [5], the authors introduced a distributed cryptographic system
that allows a set of servers to solve the PDP problem. This system is based on the integrity protected error correcting code
(IP-ECC), which improves the security and efficiency of the existing tools, like POR.
An Efficient PDP Scheme for Distributed Cloud Storage

III. PROPOSED METHOD
In this section, we introduce the principles of our cooperative provable data possession for distributed clouds,
including the main technique, model, fragment structure, index hierarchy, and the architecture to support our scheme.
A. Homomorphic Verifiable Response: A homomorphism is the map f : P → Q between two groups such that
f(g1+g2) = f(g1)×f(g2) for all g1, g2  P, where + denotes the operation in P and × denotes the operation in Q. This
notation is used to define the Homomorphic Verifiable Tags (HVTs): Given two values σi and σj for two message mi and
mj , anyone can combine them into a value σ′ corresponding to the sum of the message mi + mj.
B. Cooperative PDP: A cooperative provable data possession(CPDP) scheme S′ is a collection of two algorithms and
an interactive proof system, S′ = (K, T, P).
KeyGen(
k
1 ): It takes a security parameter k as the input, and returns a secret key sk or a public-secret key pair (pk, sk);
TagGen(sk, F,P): It takes as inputs a secret key “sk”, a file
F, and a set of cloud storage providers P = {Pk}, and returns the triples (ζ ,ψ, σ), where ζ is the secret of tags, ψ = (u,H)
is a set of verification parameters u and an index hierarchy
H for F, σ = {σ(k)}Pk∈ P denotes a set of all tags, σ(k)is the tags of the fraction F (k) of F in Pk.
Proof(P, V ): It is a protocol of proof of the data possession between the CSPs (P = {Pk }) and a verifier (V), that
is,(∑Pk∈ P Pk(F(k), σ(k)), V) (pk, ψ), where each Pk takes as input a file F(k) and a set of tags σ(k), and a public key pk
and a set of public parameters ψ is the common input between P and V . At the end of the protocol run, “ V” returns a bit
{0|1} denoting false and true where,  pPK
denotes the collaborative computing in Pk  P.
C. Fragment Structure of Cooperative PDP: We propose a fragment structure of CPDP scheme as shown in the Figure 1,
which has following characters:
 A file is split into n × s sectors and each block (or s sectors) corresponds to a tag, so that the storage of signature
tags can be reduced with the order of s.
 The verifier can check the integrity of the file by random sampling approach, which is a matter of the utmost
importance for large or huge files.
 This structure relies on the homomorphic properties to aggregate the data and tags into a constant size response,
which minimizes network communication overheads.
Figure 1: The fragment structure of Cooperative PDP model
The above structure, considered as a common representation for some existing schemes in [1][7], can be converted
to MAC-based, ECC or RSA schemes. By using BLS signatures and the random oracle model, it is easy to design a practical
CPDP scheme with the shortest homomorphic verifiable responses for public verifiability. This structure also creates
favorable conditions for the architecture of the CSPs.
D. Hash Index Hierarchy: The Architecture for data storage in distributed clouds is shown in Figure 2. This
architecture is based on a hierarchical structure with three layers to represent the relationship among all blocks for stored
resources. Three layers can be described as follows:
 First Layer (Express Layer): It offers an abstract representation of the stored resources
 Second Layer (Service Layer): It promptly offers and manages cloud storage services
 Third Layer (Storage Layer): It directly realizes data storage on many physical devices.

Figure 2: The architecture of Cooperative PDP model
This architecture naturally accommodates the hierarchical representation of the file systems. We make use of a
simple hierarchy to organize the multiple CSP services, which involve private clouds or public clouds, by shading the
differences between these clouds. As shown in Figure 2, the resources in the Express Layer are split and stored into three
CSPs in the Service Layer. In turn, each CSP fragments and stores the assigned data into the storage servers at the Storage
Layer. We distinguish different CSPs by different colors, and the denotation of the Storage Layer is the same as in Figure 1.
Moreover, we follow the logical order of data blocks to organize Storage Layer. This architecture could provide some
special functions for the data storage and management, e.g., there may exist an overlap among data blocks (as shown in
dashed line) and discontinuous blocks (as shown on a non continuous color).
IV. CONCLUSION
With the techniques such as homomorphism verifiable response and hash index hierarchy, cooperative provable
data possession (CPDP) concept has been achieved and hence integrity and availability is verified .The zero- knowledge
proof system is used and hence increases the security so it can be used widely in public cloud services thereby increasing
their performance. By this approach the computation time and as well as cost is reduced. Our system can be used as a new
method for data integrity verification in out sourcing data storage on distributed cloud environment.
REFERENCES
[1]. G. Ateniese, R. C. Burns, R. Curtmola, J. Herring, L. Kissner, Z. N. J. Peterson, and D. X. Song, “Provable data possession at
untrusted stores,” in ACM Conference on Computer and Communications Security, P. Ning, S. D. C. di Vimercati, and P. F.
Syverson, Eds. ACM, 2007, pp. 598–609.
[2]. Juels and B. S. K. Jr., “Pors: proofs of retrievability for large files,” in ACMConference on Computer and Communications
Security, P. Ning, S. D. C. di Vimercati, and P. F. Syverson, Eds. ACM, 2007, pp. 584–597.
[3]. G. Ateniese, R. D. Pietro, L. V. Mancini, and G. Tsudik, “Scalable and efficient provable data possession,” in Proceedings of the
4th international conference on Security and privacy in communication netowrks, SecureComm, 2008, pp. 1–10.
[4]. C. Erway, A. Küpç ü, C. Papamanthou, and R. Tamassia, “Dynamic provable data possession,” in ACM Conference
onComputer and Communications Security, E. Al-Shaer, S. Jha, and A. D. Keromytis, Eds. ACM, 2009, pp. 213–222.
[5]. K. D. Bowers, A. Juels, and A. Oprea, “Hail: a high-availability and integrity layer for cloud storage,” in ACM Conference on
Computer and Communications Security, E. Al-Shaer, S. Jha, and A. D. Keromytis, Eds. ACM, 2009, pp. 187–198.
[6]. Y. Dodis, S. P. Vadhan, and D. Wichs, “Proofs of retrievability via hardness amplification,” in TCC, ser. Lecture Notes in
Computer Science, O. Reingold, Ed., vol. 5444. Springer, 2009, pp. 109–127.
[7]. H. Shacham and B. Waters. Compact proofs of retrievability. In ASIACRYPT, pages 90–107, 2008.

An Efficient PDP Scheme for Distributed Cloud Storage

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