I. INTRODUCTION:

Cloud Computing has been envisioned as the next-generation architecture of IT enterprise, due to its long list of unprecedented advantages in the IT history: on-demand self-service, ubiquitous network access, location independent resource pooling, rapid resource elasticity, usage-based pricing and transference of risk. As a disruptive technology with profound implications, Cloud Computing is transforming the very nature of how businesses use information technology.

One Fundamental aspect of this paradigm shifting is that data is being centralized or outsourced into the Cloud. From users’ perspective, including both individuals and IT enterprises, storing data remotely into the cloud in a flexible on-demand manner brings appealing benefits: relief of the burden for storage management, universal data access with independent of geographical locations and avoidance of capital expenditure on hardware, software, and personnel maintenances.

As users no longer physically possess the storage of their data, traditional cryptographic primitives for the purpose of data security protection can’t be directly adopted. Thus, how to efficiently verify the correctness of outsourced cloud data without the local copy of data files becomes a big challenge for data storage security in Cloud Computing. Note that simply downloading the data for its integrity verification is not a practical solution due to the expensiveness in I/O cost and transmitting the file across the network.

II. Key policy-attribute based encryption algorithm:

Broadcast Encryption (BE) scheme is allows the sender to securely distribute a data to a dynamically changing set of users over a unsecure channel. Attribute based Broadcast Encryption (ABBE) is a excellent approach for broadcasting. Existing BE classical BE approach required an explicitly specified decrypter list. In ABBE differentiate groups of users by their attribute. In ABBE encrypter enforces an expressive access policy composed of one or more attributes. ABBE is more flexible and efficient with reduce storage overhead. Proposed algorithm is ABBE using RSA. Merge the advantage of both the algorithm. Using this scheme reduce the burden of key calculation of ABBE. RSA provide secure transmission over transmission channel. Main advantage of RSA is prime factorization. In this scheme use attribute as a prime number.

A. Concept:

In proposed system define concept is merge the advantage of ABBE less number of public key and RSA highly secure using prime number. In this paper introduce one system which will work for one or two attributes. In this system we will take attribute as a prime number. Perform operation of RSA.

B. Proposed algorithm:

KPABE using RSA. Set up for proposed algorithm

In this algorithm we use k number of attribute into the system. But here for convince this system will work for one or two attributes. Take advantage of prime numbers. Here we take attribute as a prime number.

Give one prime number as a ideal number. i.e when user don’t want to restrict by any attribute. Here in this set up we have taken two set of attributes which are describe below:

L is a list of attributes.

L={3=technical,5=nontechnical,7=regional,9= ideal }

U= unique id to each user.

a) When user joins a process for 1st time it needs to register itself with two attributes which are listed in L.

b) Each user gets an unique id during the registration process.

First sender will specify the access policy(w) for the intended receiver. Here we restrict this policy by only two attributes.

U1(w)={3,9}

N=p*q; p=3 and q=9;

Ф(n)=(p-1)(q-1)

d = e-1 mod Ф(n). e is chosen by user.

C= Me mod n;

Public key={e}

Private key={d,L}

In this proposed algorithm we change RSA public and private key as per necessary of system. At the receiver side receives ciphertext “C‟ and knows the public key. Now receiver select proper number of attributes then only receiver can calculate n and it can convert the formula M=Cd mod n into intelligible form.

III. Implementation Methodology:

After analyzing the requirements of the task to be performed, the next step is to analyze the problem and understand its context. The first activity in the phase is studying the existing system and other is to understand the requirements and domain of the new system. Both the activities are equally important, but the first activity serves as a basis of giving the functional specifications and then successful design of the proposed system. Understanding the properties and requirements of a new system is more difficult and requires creative thinking and understanding of existing running system is also difficult, improper understanding of present system can lead diversion from solution.

a) The Privacy-Preserving Public Auditing Scheme:

To effectively support public auditability without having to retrieve the data blocks themselves, we resort to the homomorphic authenticator techniques. Homomorphic authenticators are unforgeable verification metadata generated from individual data blocks, which can be securely aggregated in such a way to assure an auditor that a linear combination of data blocks is correctly computed by verifying only the aggregated authenticator. However, the direct adoption of these techniques is not suitable for our purposes, since the linear combination of blocks may potentially reveal user data information, thus violating the privacy-preserving guarantee. Specifically, if enough number of the linear combinations of the same blocks are collected, the TPA can simply derive the user’s data content by solving a system of linear equations. Overview to achieve privacy-preserving public auditing, we propose to uniquely integrate the homomorphic authenticator with random mask technique. In our protocol, the linear combination of sampled blocks in the server’s response is masked with randomness generated by a pseudo random function (PRF). With random mask, the TPA no longer has all the necessary information to build up a correct group of linear equations and therefore cannot derive the user’s data content, no matter how many linear combinations of the same set of file blocks can be collected. Meanwhile, due to the algebraic property of the homomorphic authenticator, the correctness validation of the block-authenticator pairs will not be affected by the randomness generated from a PRF, which will be shown shortly. Note that in our design, we use public key based homomorphic authenticator, specifically, the one in [11] which is based on BLS signature [16], to equip the auditing protocol with public auditability. Its flexibility in signature aggregation will further benefit us for the multi-task auditing.

b) Design Goals:

To enable privacy-preserving public auditing for cloud data storage under the aforementioned model, our protocol design should achieve the following security and performance guarantee:

1. Public auditability: to allow TPA to verify the correctness of the cloud data on demand without retrieving a copy of the whole data or introducing additional on-line burden to the cloud users.

2. Storage correctness: to ensure that there exists no cheating cloud server that can pass the audit from TPA without indeed storing users’ data intact.

3. Privacy-preserving: to ensure that there exists no way for TPA to derive users’ data content from the information collected during the auditing process.

4. Batch auditing: to enable TPA with secure and efficient auditing capability to cope with multiple auditing delegations from possibly large number of different users simultaneously.

5. Lightweight: to allow TPA to perform auditing with minimum communication and computation overhead.

Figure- 1. The proposed cloud storage model

IV. Fuzzy Search Techniques:

This fuzzy search techniques includes following three main techniques which we are using,

• Wildcard – Based Technique :

In this technique, we are using three Methods suppose we are Searching some Data File in Server and we Don’t the Exact Name. Then this Three Methods will be used for applying Fuzzy Techniques

SCASTLE, 1 = {CASTLE, *CASTLE,*ASTLE, C*ASTLE, C*STLE, CASTL*E, CASTL*, CASTLE*}.

Substitution: changing one character to another in a word.

Deletion: deleting one character from a word.

Insertion: inserting a single character into a word.

• Gram - Based Technique :

This technique is used by forming various names of File name given by User for Searching the File.

For example, the gram-based fuzzy set SCASTLE, 1 for keyword CASTLE can be constructed as

{CASTLE, CSTLE, CATLE, CASLE, CASTE, CASTL, ASTLE}.

• Symbol – Based – traverse Search Scheme :

This Technique Is used to Search the Data from Cloud Server based on the initial alphabets. Like for Cloud, If user enter file name “Cl” then also it will Retrieve Cloud File because of This Technique.

V. Proposed System:

In this project we utilize the public key based homomorphic authenticator and uniquely integrate it with random mask technique to achieve a privacy-preserving public auditing system for cloud data storage security while keeping all above requirements in mind. Extensive security and performance analysis shows that the proposed schemes are provably secure and highly efficient. We believe all these advantages of the proposed schemes will shed light on economies of scale for Cloud Computing. In this project we propose a scheme to achieve fine grainedness, data confidentiality, and scalability of organizational data in cloud. Companies can have their own separate cloud or they can get storage space from service providers such as Amazon, Google App Engine, and Microsoft Azure etc. This reduces time and work load on a organization record administration block and cost for storage.

VI. System Module and Assumption:

The implementation of the system has been described using block diagram and flow chart as follow.

Fig 2. Block Diagram

VII. APPLICATION:

1. By using privacy preserving public auditing for data storage security in cloud computing most of the computational work will be done by automatically.

2. Key generation techniques will reduce computational overhead.

3. Fuzzy techniques will helps in fine grained data access.

VIII. CONCLUSION:

Extensive security and performance analysis shows that the proposed schemes are provably secure and highly efficient. We believe all these advantages of the proposed schemes will shed light on economies of scale for Cloud Computing. In this project we propose a scheme to achieve fine grainedness, data confidentiality, and scalability of organizational data in cloud. Companies can have their own separate cloud or they can get storage space from service providers such as Amazon, Google App Engine, and Microsoft Azure etc. This reduces time and work load on a organization record administration block and cost for storage.

IX. REFERENCES:

1. P. Melland T. Grance , “Draft NIST working definition of cloud computing,” Reference on June. 3rd, 2009 Online at 2009.

2. S. Wilson, “Appengine outage,” Online at http://www.cioweblog.com/50226711/appengine php, June 2008.

3. Pascal Junod,” Alexandre Karlov” An Efficient Public-Key Attribute-Based Broadcast Encryption Scheme Allowing Arbitrary Access Policies”.

4. Yevgeniy Dodis, Nelly Fazio” Public Key Broadcast Encryption for Stateless Receivers August 1, 2002.

5. Amazon Web Services (AWS), online at http://aws. amazon.com.

Received on 12.04.2015 Accepted on 15.05.2015

Research J. Engineering and Tech. 6(2): April-June, 2015 page 301-304

DOI: 10.5958/2321-581X.2015.00046.X