
A Novel Efficient Remote Data Possession Checking Protocol in Cloud
Storage
Abstract
Cloud storage offers users scalable, flexible and high-quality data storage and computing services as an important application in cloud computing. A Novel Efficient Remote Data Possession Checking Protocol in Cloud Storage A growing number of data owners choose to outsource data files into the cloud. Because cloud storage servers are not fully trustworthy, data owners need reliable means to check possession for their files outsourced to remote cloud servers.
A Novel Efficient Remote Data Possession Checking Protocol in Cloud Storage Some remote data possession checking (RDPC) protocols have been presented to address this crucial issue. However, many existing schemes have vulnerabilities in efficiency or data dynamics. We provide a new efficient RDPC protocol based on homomorphic hash function in this paper.
Advantages
- Experiment results show that the new scheme has better performance and is practical for real applications.
- We show the advanced RDPC scheme supporting fully dynamic block operations based on ORT.
- Minimum Computation Costs.
- The data owner can perform dynamic operations of the files
Disadvantages
- Did not Support Dynamic Operations.
- Heavy Computation Cost.
- Insecure against replay attack and deletion attack.
- These schemes are either insecure or not efficient enough.
System Configuration
H/W System Configuration
Speed : 1.1 GHz
RAM : 256 MB(min)
Hard Disk : 20 GB
Floppy Drive : 1.44 MB
Key Board : Standard Windows Keyboard
Mouse : Two or Three Button Mouse
Monitor : SVGA
S/W System Configuration
Platform : cloud computing
Operating system : Windows Xp,7,
Server : WAMP/Apache
Working on : Browser Like Firefox, IE
Conclusion
We study the issue of integrity checking outsourced data files to remote server and propose an efficient, secure, data dynamic RDPC protocol. Our scheme uses a homomorphic hash function to verify the integrity of files stored on a remote server and reduce the data owner’s storage and computation costs.