AI helps you reading Science

AI generates interpretation videos

AI extracts and analyses the key points of the paper to generate videos automatically


pub
Go Generating

AI Traceability

AI parses the academic lineage of this thesis


Master Reading Tree
Generate MRT

AI Insight

AI extracts a summary of this paper


Weibo:
The reputation system we propose can help providers build content-aware trusted zones using the VMware vShield and the RSA DLP package for data traversing monitoring.6

Trusted Cloud Computing with Secure Resources and Data Coloring

IEEE Internet Computing, no. 5 (2010): 14-22

Cited: 364|Views57
EI WOS SCOPUS

Abstract

Trust and security have prevented businesses from fully accepting cloud platforms. To protect clouds, providers must first secure virtualized data center resources, uphold user privacy, and preserve data integrity. The authors suggest using a trust-overlay network over multiple data centers to implement a reputation system for establishin...More

Code:

Data:

0
Introduction
  • Trust and security have prevented businesses from fully accepting cloud platforms. To protect clouds, providers must first secure virtualized datacenter resources, uphold user privacy, and preserve data integrity.
  • Cloud security hinges on how to establish trust between these service providers and data owners.
  • The authors propose a reputation-based trust-management scheme augmented with data coloring and software watermarking.
  • PaaS further extends to the software-as-a-service (SaaS) model by creating applications on data, content, and metadata using special APIs. This implies that SaaS demands all protection functions at all levels.
Highlights
  • Trust and security have prevented businesses from fully accepting cloud platforms
  • Cloud computing enables a new business model that supports ondemand, pay-for-use, and economies-of-scale IT services over the Internet
  • Cloud platforms are dynamically built through virtualization with provisioned hardware, software, networks, and datasets
  • Cloud platform: provisioning of virtualized compute, storage, and network resources plus software and datasets from multiple data centers to satisfy the demands of multitenant applications
  • The reputation system we propose can help providers build content-aware trusted zones using the VMware vShield and the RSA DLP package for data traversing monitoring.[6]
  • The trust model Deyi Li and his colleagues propose offers a secondorder fuzzy membership function for protecting data owners.[13]. We extend this model to add unique data colors to protect large datasets in the cloud
Results
  • Privacy, and copyright protection measures needed at various cloud service levels
  • The new features the authors suggest include securing cloud computing with copyrighted content, data coloring, VM management, trust-overlay construction, and reputation systems designed for protecting data centers.
  • Securing Infrastructure as a Service The IaaS model lets users lease compute, storage, network, and other resources in a virtualized environment.
  • At the cloud infrastructure level, CSPs can enforce network security with intrusion-detection systems (IDSs), firewalls, antivirus programs, distributed denial-of-service (DDoS) defenses, and so on.
  • This level requires securing the provisioned VMs, enforcing security compliance, managing potential risk, and establishing trust among all cloud users and providers.
  • Security compliance demands that CSPs protect all data-center servers and storage areas.
  • Cloud platform: provisioning of virtualized compute, storage, and network resources plus software and datasets from multiple data centers to satisfy the demands of multitenant applications
  • Reputation systems, and data coloring for protecting cloud resources provisioned from data centers
  • Trust-overlay networks over cloud resource sites and data centers
  • Most reputation systems were designed for P2P social networking or online shopping services.[10,11] The authors can convert such systems to protect cloud platform resources or user applications on the cloud.
  • To support trusted cloud services, the authors suggest building a trust-overlay network to model the trust relationships among data-center modules.
  • This layer handles user or server authentication, access authorization, trust delegation, and data integrity control.
Conclusion
  • A trusted software environment that provides useful tools for building cloud applications over protected datasets.
  • Christian Collberg and Clark Thomborson have suggested using watermarking to protect software modules.[12] The trust model Deyi Li and his colleagues propose offers a secondorder fuzzy membership function for protecting data owners.[13] The authors extend this model to add unique data colors to protect large datasets in the cloud.
  • The authors combine the advantages of secured cloud storage and software watermarking through data coloring and trust negotiation.
  • Providers can implement the proposed reputation system and data-coloring mechanism to protect data-center access at a coarse-grained level and secure data access at a fine-grained file level.
Tables
  • Table1: Cloud platforms, reported services, and security features.*
Download tables as Excel
Funding
  • Cloud computing enables a new business model that supports ondemand, pay-for-use, and economies-of-scale IT services over the Internet
  • The Internet cloud works as a service factory built around virtualized data centers
  • Cloud platforms are dynamically built through virtualization with provisioned hardware, software, networks, and datasets
  • A lack of trust between cloud users and providers has hindered the universal acceptance of clouds as outsourced computing services
  • Proposes a reputation-based trust-management scheme augmented with data coloring and software watermarking
Reference
  • K. Hwang, G. Fox, and J. Dongarra, Distributed Systems and Cloud Computing: Clusters, Grids/P2P, and Internet Clouds, Morgan Kaufmann, to appear, 2010.
    Google ScholarFindings
  • K. Hwang, S. Kulkarni, and Y. Hu, “Cloud Security with Virtualized Defense and Reputation-Based Trust Management,” IEEE Int’l Conf. Dependable, Autonomic, and Secure Computing (DASC 09), IEEE CS Press, 2009.
    Google ScholarLocate open access versionFindings
  • J. Nick, “Journey to the Private Cloud: Security and Compliance,” tech. presentation, EMC, Tsinghua Univ., 25 May 2010.
    Google ScholarFindings
  • S. Song et al., “Trusted P2P Transactions with Fuzzy Reputation Aggregation,” IEEE Internet Computing, vol. 9, no. 6, 2005, pp. 24–34. 5. “Security Guidance for Critical Areas of Focus in Cloud Computing,” Cloud Security Alliance, Apr. 2009; www. cloudsecurityalliance.org/guidance/csaguide.v2.1.pdf. http://cise.aip.org www.computer.org/cise
    Locate open access versionFindings
  • 6. T. Mather, S. Kumaraswamy, and S. Latif, Cloud Security and Privacy: An Enterprise Perspective on Risks and Compliance, O’Reilly Media, 2009.
    Google ScholarFindings
  • 7. J. Rittinghouse and J. Ransome, Cloud Computing: Implementation, Management and Security, CRC Publisher, 2010.
    Google ScholarFindings
  • 8. X. Lou and K. Hwang, “Collusive Piracy Prevention in P2P Content Delivery Networks,” IEEE Trans. Computers, July 2009, pp. 970–983.
    Google ScholarLocate open access versionFindings
  • 9. C. Clark et al., “Live Migration of Virtual Machines,” Proc. Symp. Networked Systems Design and Implementation, 2005, pp. 273–286.
    Google ScholarLocate open access versionFindings
  • 10. L. Xiong and L. Liu, “PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities,” IEEE Trans. Knowledge and Data Eng., July 2004, pp. 843–857.
    Google ScholarLocate open access versionFindings
  • 11. R. Zhou, and K. Hwang, “PowerTrust: A Robust and Scalable Reputation System for Trusted Peer-to-Peer Computing,” IEEE Trans. Parallel and Distributed Systems, Apr. 2007, pp. 460–473.
    Google ScholarLocate open access versionFindings
  • 12. C. Collberg and C. Thomborson, “Watermarking, Tamper-Proofing, and Obfuscation-Tools for Software Protection,” IEEE Trans. Software Eng., vol. 28, 2002, pp. 735–746.
    Google ScholarLocate open access versionFindings
  • 13. D. Li, C. Liu, and W. Gan, “A New Cognitive Model: Cloud Model,” Int’l J. Intelligent Systems, Mar. 2009, pp. 357–375.
    Google ScholarLocate open access versionFindings
  • 14. D. Li and Y. Du, Artificial Intelligence with Uncertainty, Chapman & Hall, 2008. Kai Hwang is a professor of computer engineering at the University of Southern California and an IV-endowed visiting professor at Tsinghua University, China. He specializes in computer architecture, parallel processing, Internet security, and cloud computing. Hwang has a PhD from the University of California, Berkeley. He’s the founding editor in chief of the Journal of Parallel and Distributed Computing and a fellow of IEEE. Contact him at kaihwang@usc.edu.
    Google ScholarLocate open access versionFindings
  • Selected CS articles and columns are also available for free at http://ComputingNow.computer.org.
    Findings
Author
0
Your rating :

No Ratings

Tags
Comments
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn