A Secured Distributed and Data Fragmentation Model for Cloud Storage
- 10.2991/isccca.2013.159How to use a DOI?
- cloud storage, secured, OpenID, OAuth, data fragmentation, Haystack
The increasing popularity of cloud service is leading people to concentrate more on cloud storage than traditional storage. However, cloud storage confronts many challenges, especially, the security of the out-sourced data(the data that is not stored/retrieved from the tenants’ own servers). Security not only can keep the data from attacking but also can recover the original data after attack efficiently. Thus, to address the security issue, we proposed a new distributed and data fragmentation model of cloud storage named DDFM (Distributed and Data Fragmentation Model). DDFM aims to provide tenants a secured and integrated cloud storage service with layer-to-layer protection strategy. The layer-to-layer protection strategy of our model includes three main algorithms: the Authentication and Authorization Management Algorithm based on OpenID and OAuth, the Data Fragment Algorithm based on Granular Computing and the Haystack File Storage Algorithm. Considering tenants' security requirement our model DDFM based on these algorithms provided a better decision of cloud storage architecture for our tenants. Furthermore, DDFM can defense most of the network threats and provide a secured way for the third-party applications to access sensitive information that stored on the cloud storage.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Lixuan Wang AU - Lifang Liu AU - Shenling Liu AU - Dong Chen AU - Yujiao Chen PY - 2013/02 DA - 2013/02 TI - A Secured Distributed and Data Fragmentation Model for Cloud Storage BT - Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013) PB - Atlantis Press SP - 633 EP - 638 SN - 1951-6851 UR - https://doi.org/10.2991/isccca.2013.159 DO - 10.2991/isccca.2013.159 ID - Wang2013/02 ER -