# Data Integrity and Dynamic Storage Way in Cloud Computing

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4 4 user control. Then, G= {n i,.. n i+1,. n (i-m) } and The following equations explain it in clear way as, 1) n ϵ G, n, here n>1>0 where G is cloud level identification and n is number of server from user level. 2) n={i a, i a+1,.. i a-n }, where a is data counting for n server. 3) n={{r i { i a, i a+1,.. i a-n },R i+1 {i a, i a+1, i a-n }, R i-n { i a, i a+1,.. i a- n}}, where R is the number of different server divided into the cloud. 4) n, n= (R 1i,..R 2i, R n-i ), it is up to the R number of server count 5) i, i=any data in G and while checking for integrity it gets n=>r formation. It means that n implies R in all manners. B. Algorithm in User Level 1: //Let G be the storage or cloud 2: // N the total number of server 3: //Input n and I for server and counter 4: //G={n i,n i+1,..,(n i-n -1)} 5: //if(n<=g)&&(n==g) 6: { 7: for(i=0;i<=n;i++) 8: S=i; 9: S++; 10: } 11: else if 12: (n==r) 13: { 14: or (i=0;i<=n;i++) 15: { 16: n++; 17: } 18: stop the program. C. Checking for Same Data in User and Cloud Level Initially we should assume for Boolean value for true and false condition by comparing both user and cloud level data. Then, 1) Verify (Z i ={G 1i (true)g 2i (false)}) Check for condition, 2) if the condition G 1i = G 2i then it is true in such a way that, 3) n==n u it is set that Z={s(true)} n!=n u otherwise, 4) Z=={s(false)}. These are the conditions for maintaining the user and cloud level data integrity for all user and server data, since the case has the above condition every user and cloud lever data comparison has different. D. Data Verifiability in Cloud Server Level after Upload Here as we did before in our user level part the same procedure is followed. The only difference is that all processes are done in cloud server location using verification protocol or data reading protocol. The changes can be as in following manner. Assume that G u =>G. It is done for same data identification among user and server level data content. Then G u uploaded data into the cloud server. 1) n u ϵg u, n u, here n u >1>0 where G u is cloud level identification and n is number of server from user level. 2) n u ={i a, i a+1,.. i a-n }, where a is data counting for n server. 3) n u ={{R i { i a, i a+1,.. i a-n },R i+1 { i a, i a+1,.. i a-n },.R i-n { i a, i a+1,.. i a-n }}, where R is the number of different server divided into the cloud. 4) n u, n u =(R 1i,R 2i, R n-i ), it is up to the R number of server count. 5) i u, i=any data in G u and while checking for integrity it gets n u =>R formation. It means that n u implies R in all manners. E. Algorithm in Cloud Server Level 1://Let G be the storage or cloud 2:// N the total number of server 3://Input n and I for server and counter 4://G={n i,n i+1,..,(n i-n -1)} 5://if(n<=G)&&(n==G) 6:{ 7:for(i=0;i<=n;i++) 8:S=i; 9:S++; 10:} 11:else if 12:(n==R) 13:{ 14:for (i=0;i<=n;i++) 15:{ 16:n++; 17:} F. Putting Server Restore Access Point for Data Recovery When server failure happens all data may be lost its integrity and since user doesn t have the local copy of data there is no more possibility to recover the already lost data from its previous original condition. So here we have modeled one scheme multi-server data comparison algorithm for every data upload for the purpose of data recovery access point in every data update by user. This prevents entire system collapse from data lose against any such type of system crash including Byzantine, and related internal and external problem. The above scheme explains the server crash breaking condition in efficient manner by putting one restore access point in previously updated data from user. 1) Assume server access point for already stored data, X and after the server failure 2) Put automatic restore point then, 3) Compare for previous value with current total value. Now the previous value is as, => n i=0 [(S d +T d )] d-1 =X 4) Current value before crash is as, => n i=0[(s d +S d 1)+(T d +T d 1)]=Y 5) Now when we do comparison for both X and Y, the following assumptions are made as, =>X>Y or X<Y then do update otherwise if X==Y then restore to the same condition. Here this formula is applied for overall data from the server by receiving user and server level data. Here S is the cloud

6 6 implement the locking protocol in cloud data storage with the help of CSP for data update. It can give clear security to user s own data when users complete his requirement. REFERENCES [1] Enabling Public Verifiability and Data Dynamics for Storage Security in Cloud Computing Qian Wang1, Cong Wang1, Jin Li1, Kui Ren1, and Wenjing Lou2-Springer-Verlag Berlin Heidelberg [2] Cloud security defence to protect cloud computing against HTTP-DoS and XML-DoS attacks, Ashley Chonka,YangXiang n, WanleiZhou, AlessioBonti, Elsevier. [3] A Multiple-Replica Remote Data Possession Checking Protocol with Public Verifiability-2010 Second International Symposium on Data, Privacy, and E-Commerce.E. H. Miller, A note on reflector arrays (Periodical style Accepted for publication), IEEE Trans. Antennas Propagat., to be published. [4] Amazon.com, Amazon s3 availability event: July 20, 2008, Online at July [5] Sun Microsystems, Inc., Building customer trust in cloud computing with transparent security, Online at November M. Young, The Techincal Writers Handbook. Mill Valley, CA: University Science, [6] Addressing cloud computing security issues, Future generation computer systems(2011) [7] G. Ateniese, R. Burns, R. Curtmola, J. Herring, L. Kissner, Z. Peterson, and D. Song, Provable data possession at untrusted stores, in Proc. of CCS 07, Alexandria, VA, October 2007, pp [8] Towards Secure and Dependable Storage Services in Cloud Computing Cong Wang, Student Member, IEEE, Qian Wang, Student Member, IEEE, Kui Ren, Member, IEEE, Ning Cao, Student Member, IEEE, and Wenjing Lou, Senior Member, IEEE Dinesh.C is a post graduate student pursuing Computer Science and Engineering from MAILAM ENGINEERING COLLEGE under ANNA UNIVERSITY OF TECHNOLOGY. His area of interest is security and privacy in Cloud Computing, and Secure Mobile Cloud as well as Cryptography and Network security. He is currently doing his project in cloud computing area, and has published one international journal, International Journal of Computer Applications ( ) Volume 31 No.6, October 2011, in Cloud Computing.

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