Defense Date

2012

Document Type

Thesis

Degree Name

Master of Science

Department

Computer Science

First Advisor

Meng Yu

Abstract

Cloud computing has changed how services are provided and supported through the computing infrastructure. It has the advantages such as flexibility , scalability , compatibility and availability . However, the current architecture design also brings in some troublesome problems, like the balance of cooperation benefits and privacy concerns between the cloud provider and the cloud users, and the balance of cooperation benefits and free-rider concerns between different cloud users. Theses two problems together form the incentive problem in cloud environment. The first conflict lies between the reliance of services and the concerns of secrets of cloud users. To solve it, we proposes a novel architecture, NeuCloud, to enable partially, trusted, transparently, accountably privacy manipulation and revelation. With the help of this architecture, the privacy-sensitive users can be more confident to move to public clouds. A trusted computing base is not enough, in order to stimulate incentive-compatible privacy trading, we present a theoretical framework and provide the guidelines for cloud provider to compensate the cloud user's privacy-risk-aversion. We implement the NeuCloud and evaluate it. Moreover, a improved model of NeuCloud is discussed. The second part of this thesis strives to solve the free-rider problem in cloud environment. For example, the VM-colocation attacks have become serious threats to cloud environment. We propose to construct an incentive-compatible moving-target-defense by periodically migrating VMs, making it much harder for adversaries to locate the target VMs. We developed theories about whether the migration of VMs is worthy and how the optimal migration interval can be determined. To the best of our knowledge, our work is the first effort to develop a formal and quantified model to guide the migration strategy of clouds to improve security. Our analysis shows that our placement based defense can significantly improve the security level of the cloud with acceptable costs. In summary, the main objective of this study is to provide an incentive-compatible to eliminate the cloud user's privacy or cooperative concerns. The proposed methodology can directly be applied in commercial cloud and help this new computing fashion go further in the history. The theoretical part of this work can be extended to other fields where privacy and free-rider concerns exist.

Rights

© The Author

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

May 2012

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