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Integration of Data Possession on Cloud
Nithish Kumar.V
1, Gopirajan.P.V
21P.G Student, Department of Computer Science and Engineering, Karpaga Vinayaga College of Engineering and Technology, Chinakolambakkam, Padalam, Tamil Nadu, India
2Department of Computer Science and Engineering, Karpaga Vinayaga College of Engineering and Technology, Chinakolambakkam, Padalam, Tamil Nadu, India
Abstract: Secured applications are stored in cloud computing, cloud service providers are given more secure storage, flexibility, and high efficient data retrieve from cloud. A growing number of data owners choose to outsource data files to the cloud. Because cloud storage servers are not fully trustworthy, nowadays technology are moving very fast and new technics updated regularly at the same time data owners always depends cloud computing environments for their outsourcing data files.
Similarly hackers is hacking our data very smart in this reasonable most of the data owners not trustworthy cloud platforms. Frequently data owners check the possession for their files where they were given outsourced to remote cloud servers.
We identified in this crucial problem and represent new techniques for remote data possession checking protocols. We introduce pro-efficient RDPC protocol belongs to homomorphic hash function. In this new approach is proof high efficient security against any attack. we can easily find the location of our files using Merkle Hash Tree and data owners can always checks their cloud data is secure or not. It supports dynamic transaction on file blocks. it reduces the computation and communication cost while between two or more file transactions and also it given reliable experiments result for any outsourcing real applications.
Here another one more options are given third party can do verification many times comparison between user's data and originals data stored in the cloud.
Key Words: RDPC Protocols, ORT, Hash Function, Cloud Security.
I. INTRODUCTION
loud computing is a distributed computing environment we can store N-number of data and files secure and also access any from the world via internet while uploading, downloading and sharing should maintain secret key for possessive data on cloud[1]. Most of the software industry is used real time software application because it gives more reliable, scalable security, user friendly and low cost communication from one place to another place [2]. Attribute based encryption (ABE) is faced major issue user revocation ABC scheme does not give any guarantee for cloud storage system. Introduced cipher text policy attribute based encryption (CP-ABE) scheme and achieved efficiently user revocation issues for cloud storage system. in this scheme prove it high security by using Diffie Hellman and it shows experiment results computation cost for local devices is low it is appropriate for resource constrained devices[3]. Chosen plaintext attack (CPA) is facing the data owner uploading and sharing data on cloud. Cloud service providers (CSP) perform partial encryption and decryption without knowing anything
about KSF-OABE [4]. cloud environments is facing two important issues for user revocation and key update in order to overcome these two issues introduce new concept is Searchable Cipher Text Policy Attribute Based Encryption(SCPABE). it is high security and reduced assumption of DBDH and DL[5] they were introduced Decentralized key policy ABE techniques every authorized people has been issue the secret key to user. the user doesn't know any information about global identifier. They were used DBDH and does not require more than one authorities. User can join and leave easily from global identifiers and no centralized authorization [6]. They have been achieved good performance using through protocols it supports verify the public without helping third party auditors. It gives more reliable and guarantees private information in third party verifiers and also secured protocols [7]. They have been introduced PRSE based on the user interaction and scoring result. Data owner control the user search keywords and showing updated result very efficient and effectively [8]. They have been proposed multi keyword ranked search over encrypted data which is supports dynamically update, insert and delete records. Also introduced tree based indexed structure and Greedy Depth first Search, KNN algorithm is used secure encrypt index and vectors it gives accurate score calculation for relevant user activities[9]. They have been introduced MVPDP system which is related to homomorphic function. It is stateless and independent of cloud
Storage it is more efficient compare to other PDP systems.
Here bilinear operation does not require [10]. it is achieved two things one is stored multiple cloud servers and save the verifiers cost they have been introduced novel techniques IDDPDP it proof efficient and flexible and also realize private, public and delegated verification[11]. In this approach is mainly concentrating on while uploading multiple cloud servers getting acknowledgement from CSP. And also it supports dynamic operation such as insert, delete, append.
Authorized users can get file copy from the CSP [12]. They were found forgery attack and replace attack by a malicious server in cloud computing environment. They have been introduced and proposed improved dynamic RDPC protocol.
It supports private verification, N-number of auditing integrity checking and dynamic operation. In this protocol proved efficient security model [13]. Data owners found the replication from the multiple servers some scenarios updated twice or more than one time. In this scenario CSP can charge more from data owners. Data owner is made service level
C
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agreements between data owner and CSP. It is compareoriginal files, updated files and duplicated files. It is proposed new techniques of DMR-PDP supports dynamic operations from any server. In this approach highly secure than other techniques [14]. They introduced new concept for CPDP satisfied security soundness. Here organizer generates valid response where data owner stored data. Added two new security concept is origin, severity, it gives reliable and more secure [15].
II. PRELIMINARIES A. Homomorphic Hash Function
The input parameters of key generation algorithm is KeyGen(λp,λq,m,s),Where K-is used homomorphic key values, λp and λq are security parameters, m is count the total number of message and s is random seed. Output parameters of homomorphic function is K=(p,q,ḡ) Where p and q are two random big primes properties |p|=λp and |q|=λq and q|(p-1), ḡ=[g1,g2,g3,g4,…gm].
B. Operation Record Table
It is support dynamic behaviors of the file operations such as insert delete, modify and so on. It has three types of columns like Block Position (BP), Block Index (BI) and Block Version (BV).
Block Position (BP) it is indicate current block of the file then its index value automatically increment by 1. Block Index (BI) it is represent logical index position of the current block of the file section. Block Version (BV) indicates current version of the block of file when concrete block update anything its value will be incremented by 1.
C. Outline for CSS and Data owner
The CSS is a storage device and it received the request from data owners and checks their acknowledgement. The CSS is distributed outsourced data files once acknowledgement correct.
III. RDPC PROCEDURE A. Algorithm:
KeyGen(1k,λp,λq,m,s) (K,sk) security parameters are k, λp, λq, m is message counter and random seed is s. K=(p, q, ḡ) where ḡ=[g1,g2,g3,g4,…gm], sk€ Z*p data owner has K and sk private.
TagGen(K,sk,F) T. where F is a upload File. Data owner first split F into n blocks
F={F1,F2,F3,…Fn}.
Challenge(c) chal. The data owner picks two random numbers k1, k2 € Z*p and send challenges chal=(c, k1, k2) to CSS.
ProofGen(F,T, chal) P. CSS receives the challenge chal=(c,k1,k2) from data owner and calculate challenge set C={(vi, ai)} where vi=π(k1,i), ai = ɸ(k2,i)for 1≤ i ≤c.
Verify (K,sk,chal,P){1,0}received proof from the CSS, data owner calculates vi=π(k1,i), ai = ɸ(k2,i) and hvi =h(Fid || n || m||
vi).
Fig.1. Architecture of RDPC Protocol B. Dynamic Procedure of RDPC
PrepareUpdate (Fi’, i, UT)
In this algorithm handle three types of dynamic operation such as insert, modify and delete. It has different type of parameter can pass.
PrepareUpdate (Fi’, i, insert) URI insert new record into the database. UT is insert parameter. Fi’ is indicates new block to be insert and i is the position of new block.
PrepreUpdate (Fi’, i, modify) URI modify the existing file content or record.
PrepareUpdate (null, i, delete) URI data owner delete a particular content from the file (i+1) row tail order.
Fig.2.ORT Operations
ExecUpdate(URI) {Success, Fail} data owner did any operation on file block finally CSS receives the updates from data owners. CSS replace the existing content and updating new content when complete the work properly the CSS return success to the data owner otherwise returns Fail.
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IV. EXPERIMENTAL RESULTSFig.3. Home Page
Fig.4. Login Page
Fig.5. Data Owner responsibilites
Fig.6.Uploading File & Generating key
Fig.7.Uploading File Block
Fig.8.Uploading file local drive to cloud
Fig.9.Data possession challenge
Fig.10.View challenges
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Fig.11.Data possession Proof
Fig.12.Proof verification
Fig.13.Dynamic operations
Fig.14. Insert Operation
Fig.15. Modify operation
Fig.16. Delete Operation
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Fig.17.Download files V. PERFORMANCE ANALYSIS
Computation cost- Tmul, Texp, Tprf, Tprp, Thash, Tadd these function indicates time of cost, multiplication, modular exponentiation, pseudo-random number generation, permutation operation, hash operation and addition operations. CSS is depends the ProofGen algorithm for computation cost. Which is cTprp + cTprf + (2c-1) Tmul + (c-1) Tadd + cTexp in total.
Storage cost
A data owner has only homomorphic key, private key, and the ORT. Which is upper bound 2 |p| + (m+1)|q| +12n. CSS storage cost is divide into two parts 1. file and 2. Tags final upper bound of storage cost of CSS nm|q|+n|p|.
Communication cost
Data owner send a challenges chal=(c, k1, k2) to CSS. CSS returns acknowledge or proof
𝐹 , 𝑇
to data owner.Communication cost for the challenge is logc +(m+2) |q| +|p|.
COMPARISON OF DIFFERENT RDPC SCHEME
Here compare our scheme to other RDPC procedure following table:
Analysis result
Fig.19. setup time and cost
Fig.20. computation cost of proof generation
Fig.21. Time cost for different types of ORT VI. CONCLUSION
We studied major issue for integrity checking of data file where we stored in remote and outsourced files our scheme homomorphic hash function is used to check and verify integrity for the files on CSS. In this function reduces over all communication, storage and computation costs of the data owner. Our architecture is lightweight and dynamic operation by using ORT. We also proof security and efficiency for our experiments results.
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