ENABLING DATA INTEGRITY PROTECTION IN
REGENERATING-CODING-BASED CLOUD STORAGE: THEORY AND IMPLEMENTATION
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ABSTRACT:
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.
EXISTING SYSTEM:
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:
v Data
have been accidentally corrupted or maliciously compromised by insider/outsider
attacks..
v Security
concerns arise when data storage is outsourced to third party cloud storage
providers.
v Data
corrupted due to server failures.
PROPOSED
SYSTEM:
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:
v
FMSR-DIP codes, which enable integrity protection,
fault tolerance, and efficient recovery for cloud storage.
v
Using several cryptographic primitives.
v
Lost data founded easily.
SYSTEM CONFIGURATION:-
HARDWARE REQUIREMENTS:-
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
SOFTWARE
REQUIREMENTS:
Operating
system : Windows XP.
Coding
Language : .Net
Data
Base : SQL Server 2005
Tool : VISUAL STUDIO 2008.
REFERENCE:
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
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