- PRIVACY-PRESERVING PUBLIC AUDITING FOR DATA STORAGESECURITY IN CLOUD COMPUTING
PRIVACY-PRESERVING PUBLIC AUDITING FOR DATA STORAGESECURITY IN CLOUD COMPUTING
PRIVACY-PRESERVING PUBLIC AUDITING FOR DATA STORAGESECURITY IN CLOUD COMPUTING.
- 1. PRIVACY-PRESERVINGPUBLIC AUDITING FOR DATASECURITY IN CLOUDCOMPUTINGBy,STORAGES.Kayalvizhi Sharmila
2. ABSTRACT Cloud Computing, enabling convenient networkaccess to a shared pool of configurable computingresources Enabling public auditability, so that users can resortto an external audit party to check the integrity ofoutsourced data when needed. TPA audit the cloud data storage withoutdemanding the local copy of data, and introduce noadditional on-line burden to the cloud user. 3. OUR CONTRIBUTIONThe scheme supports an external auditor to auditusers outsourced data in the cloud without learningknowledge on the data content.Achieves batch auditing where multiple delegatedauditing tasks from different users can beperformed simultaneously by the TPA.To prove the security and justify the performance ofproposed schemes through concrete experimentsand comparisons with the state-of-the-art. 4. THIRD PARTY AUDITOR (TPA) Third Party Auditor (TPA) TPA helps the user to audit the data To allow TPA securely: 1) TPA should audit the data from the cloud, not ask for a copy 2) TPA should not create new vulnerability to user data privacy This paper presents a privacy-preserving public auditingsystem for cloud data storageDataCloud networkuseruseruserExternalAudit party 5. ARCHITECTURE 6. DESIGN GOALSI. Public auditabilityII. Storage correctnessIII. Privacy-preservingIV. Batch auditingV. Lightweight 7. THE EXISTING SYSTEM 8. THE PROPOSED SCHEME We utilize the public key based homomorphicauthenticator and uniquely integrate it with randommask technique. TPA can perform multiple auditing taskssimultaneously. Four algorithmsKeyGen, SigGen, GenProof, VerifyProof. 9. FIG: PROPOSED SYSTEM 10. PRIVACY-PRESERVING PUBLIC AUDITING MODULE: Homomorphic authenticators are unforgeableverification metadata.Homomorphic authenticatorBlock 1 Block 2 Block kVerificationMetadataVerificationMetadataVerificationMetadataAggregate VerificationMetadataA linear combination of data blocks can be verified bylooking only at the aggregated authenticator 11. 11SetupAudituser KeyGenPublic & SecretparametersSigGen File FVerificationMetadataTPATPA issues an audit message or a challenge to CSPGenProofVerifyProofCSPTPAFile FResponse messageVerification MetadataPhases 12. MORE EXTENSIONS Batch auditing There are K users having K files on the same cloud They have the same TPA Then, the TPA can combine their queries and save incomputation time The comparison function that compares the aggregateauthenticators has a property that allows checking multiplemessages in one equation Instead of 2K operation, K+1 are possible Data dynamics The data on the cloud may change according to applications This is achieved by using the data structure Merkle Hash Tree(MHT) With MHT, data changes in a certain way; new data is added insome places There is more overhead involved ; user sends the tree root toTPA 13. CONCLUSION Utilizing the homomorphic authenticator andrandom mask technique to guarantee that TPAwould not learn any knowledge about the datacontent Considering TPA may concurrently handle multipleaudit sessions from different users for theiroutsourced data files