A Flexible Authentication Scheme with Supporting Multiple Granularity of Data Integrity

Long Chen; Xiao Yin Yi

doi:10.4028/www.scientific.net/AMM.536-537.489

Paper Titles

The Application of Immune Genetic Algorithm in Parallel Sorting
p.466

Forecast of Short-Term Wind Power Based on GA Optimized Elman Neural Network
p.470

Knowledge-Base Constrained Optimization Evolutionary Algorithm and its Applications
p.476

The Research of the Optimization Model of Flight Scheduling Based on Filtered Beam Search
p.481

A Flexible Authentication Scheme with Supporting Multiple Granularity of Data Integrity
p.489

A Method of Heterogeneous Data Integration Based on SOA
p.494

A Novel Change-Point Detection Approach for Monitoring High-Dimensional Traffics in Distributed Systems
p.499

A Query Optimization Technology Based on Data Partition
p.512

A Web Text De-Noising Algorithm Based on Machine Learning
p.516

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 536-537A Flexible Authentication Scheme with Supporting...

A Flexible Authentication Scheme with Supporting Multiple Granularity of Data Integrity

Abstract:

To extend the flexibility of data integrity verification method,adapted to the different verification environment, proposed an improved solution that can support multi-granularity.It organizes files into three kinds of granularity such as data blocks,data sub-blocks and basic-blocks,basic-block realize data gathered to form data sub-block.Sign in the data sub-block,using signature of the sub-block to generate signature of block. Improvement program can achieve the verification of data blocks and sub-blocks. Validation of data block can reduce the data traffic in the validation process,two particle combination can improve the overall efficiency.In the proposed layered merkel hash tree is put forward,the dynamic operation can be supported by the sub-block or the block.Securitycommunication performance analysis show that the improvement program is effective and has a better practicability

You might also be interested in these eBooks

Advances in Mechatronics, Robotics and Automation II

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 536-537)

Pages:

489-493

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.536-537.489

Citation:

Cite this paper

Online since:

April 2014

Authors:

Long Chen, Xiao Yin Yi

Keywords:

Cloud Computing, Data Integrity, Dynamic Operation, Granularity, Signature

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

References

[1] G. Ateniese, R. Burns, R. Curtmola, J. Herring, L. Kissner,Z. Peterson, D. Song, Provable data possession at untrusted stores[C]. in Proc. of CCS'07, Alexandria, VA, 2007, p.598–609.

DOI: 10.1145/1315245.1315318

Google Scholar

[2] Chen Long, Wang Guo-yin. A fine-grained data integrity verification method[J]. Chinese Journal of software, 2009, 20(4): 902-909.

Google Scholar

[3] Cong Wang, Qian Wang, Kui Ren, Wenjing Lou. Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing [C]. INFOCOM, 2010 Proceedings IEEE. IEEE, 2010: 1-9.

DOI: 10.1109/infcom.2010.5462173

Google Scholar

[4] Qian Wang, Cong Wang, Jin Li, Kui Ren, Wenjing Lou. Enabling public verifiability and data dynamics for storage security in cloud computing [M]. Computer Security–ESORICS 2009. Springer Berlin Heidelberg, 2009: 355-370.

DOI: 10.1109/iwqos.2009.5201385

Google Scholar

[5] C. Erway, A. Kupcu, C. Papamanthou, and R. Tamassia. Dynamic provable data possession[J]. in Proc. of CCS'09. Chicago, IL, USA: ACM, (2009).

DOI: 10.1145/1653662.1653688

Google Scholar

[6] D. Boneh, B. Lynn, H. Shacham. Short Signatures from the Weil Pairing[C]. Proc. of Cryptology -Asiacrypt'2001. London, UK: Springer-Verlag, 2001: 514-532.

DOI: 10.1007/3-540-45682-1_30

Google Scholar

[7] Ari Juels and Burton S. Kaliski Jr., Pors: proofs of retrievability for large ﬁles[C]. Proceedings of the 14th ACM conference on Computer and communications security. ACM, 2007: 584-597.

DOI: 10.1145/1315245.1315317

Google Scholar

[8] Chen Long, Li Junzhong. A Verifiable Method for Remote Data Integrity Supporting Different Granular Operation[J]. Journal of Jilin University. 2012. 42(1). pp: 295-299.

Google Scholar