SaaS application is becoming more and more popular with the development of the cloud computing. In order to use the cloud service, the tenants should upload their data to the databases of cloud service provider, so how to protect the tenants’ privacy information from snooping or leaking by DBA while keeping a good application performance is a big challenge. Therefore, we address this challenge by proposing a novel cloud data fragmentation cluster-based privacy preserving mechanism in this paper, the mechanism could give an optimal privacy preserving strategy by clustering relevancy matrix using Bond Energy Algorithm and partitioning the clustered matrix according to the privacy constraints proposed by the tenants.
목차
Abstract 1. Introduction 2. Related Work 3. Cloud Data Fragmentation Privacy Preserving Management Framework 4. Realization of Cloud Data Fragmentation Privacy Preserving Mechanism 4.1. Related Concept 4.2. Attribute Relevancy Cluster based Data Fragmentation Algorithm 4.3. Privacy Preserving Strategy Optimal Proof 5. Experiments 6. Summarize Acknowledgements References
키워드
cloud computingSaaSBond Energy Algorithmprivacy preserving strategy
저자
Yali Shao [ School of Computer Science and Technology, Shandong University, Jinan, China ]
Yuliang Shi [ Yuliang Shi | School of Computer Science and Technology, Shandong University, Jinan, China ]
Corresponding author
Hui Li [ School of Computer Science and Technology, Shandong University, Jinan, China ]
보안공학연구지원센터(IJGDC) [Science & Engineering Research Support Center, Republic of Korea(IJGDC)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Grid and Distributed Computing
간기
격월간
pISSN
2005-4262
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Grid and Distributed Computing Vol.7 No.4