ENABLING DATA INTEGRITY PROTECTION IN REGENERATING-CODING-BASED CLOUD STORAGE: THEORY AND IMPLEMENTATION
To protect outsourced data in cloud storage against corruptions, adding fault tolerance to cloud storage, along with efficient data integrity checking and recovery procedures, becomes critical. Regenerating codes provide fault tolerance by striping data across multiple servers, while using less repair traffic than traditional erasure codes during failure recovery. Therefore, we study the problem of remotely checking the integrity of regenerating-coded data against corruptions under a real-life cloud storage setting. We design and implement a practical data integrity protection (DIP) scheme for a specific regenerating code, while preserving its intrinsic properties of fault tolerance and repair-traffic saves. Our DIP scheme is designed under a mobile Byzantine adversarial model, and enables a client to feasibly verify the integrity of random subsets of outsourced data against general or malicious corruptions. It works under the simple assumption of thin-cloud storage and allows different parameters to be fine-tuned for a performance-security trade-off. We implement and evaluate the overhead of our DIP scheme in a real cloud storage testbed under different parameter choices. We further analyze the security strengths of our DIP scheme via mathematical models. We demonstrate that remote integrity checking can be feasibly integrated into regenerating codes in practical deployment.
One major use of cloud storage is long-term archival, which represents a workload that is written once and rarely read. While the stored data are rarely read, it remains necessary to ensure its integrity for disaster recovery or compliance with legal requirements. Since it is typical to have a huge amount of archived data, whole-file checking becomes prohibitive. Proof of retrievability (POR) and proof of data possession (PDP) have thus been proposed to verify the integrity of a large file by spot checking only a fraction of the file via various cryptographic primitives.
DISADVANTAGES OF EXISTING SYSTEM:
vData have been accidentally corrupted or maliciously compromised by insider/outsider attacks..
vSecurity concerns arise when data storage is outsourced to third party cloud storage providers.
vData corrupted due to server failures.
we design and implement a practical data integrity protection (DIP) scheme for regenerating-codingbased cloud storage. We augment the implementation of functional minimum-storage regenerating (FMSR) codes and construct FMSR-DIP codes, which allow clients to remotely verify the integrity of random subsets of long-term archival data under a multiserver setting. FMSR-DIP codes preserve fault tolerance and repair traffic saving as in FMSR codes. Also, we assume only a thin-cloud interface, meaning that servers only need to support standard read/ write functionalities. This adds to the portability of FMSRDIP codes and allows simple deployment in general types of storage services. By combining integrity checking and efficient recovery, FMSR-DIP codes provide a low-cost solution for maintaining data availability in cloud storage.
ADVANTAGES OF PROPOSED SYSTEM:
vFMSR-DIP codes, which enable integrity protection, fault tolerance, and efficient recovery for cloud storage.
vUsing several cryptographic primitives.
vLost data founded easily.
Processor - Pentium –IV
Speed - 1.1 Ghz
RAM - 512 MB(min)
Hard Disk - 40 GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - LCD/LED
Operating system : Windows XP.
Coding Language : .Net
Data Base : SQL Server 2005
Tool : VISUAL STUDIO 2008.
Henry C.H. Chen and Patrick P.C. Lee, “Enabling Data Integrity Protection in Regenerating-Coding-Based Cloud Storage: Theory and Implementation” IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 25, NO. 2, FEBRUARY 2014