UC Merced

The emerging field of Cloud Computing provides elastic on-demand services over the Internet or over a network. According to the International Data Corporation (IDC), cloud computing has two major issues: i) architecture issues, such as a lack of standardization, a lack of customization; and ii) users’ data privacy. In this study we focus on these issues.

We are facing an increasing demand for migration of varieties of traditional databases and computation services to cloud computing environments, i.e., database-as-a-service. Although each service offers a new feature, it escalates standardization and customization issues due to the lack of standardization between cloud vendors and service customization because each cloud-based service has its own features, requirements and outputs. In the first part of this study, we propose a cloud architecture based on a Service-Oriented Architecture (DCCSOA) that enhances our ability to do standardization and customization in the cloud. The proposed architecture uses a single layer, which is called Dynamic Template Service Layer (DTSL), that provides the following operations and advantages:

i) enables a single service layer to interact with all native cloud services (e.g., IaaS, PaaS, SaaS and any cloud-based services);

ii) provides a standardization for existing services and future services in the cloud;

iii) customizes native cloud services based on users’ group requests.

The second part of this study focuses on users’ data privacy preservation on the proposed architecture. Users’ data privacy can be violated by the cloud vendor, the vendor’s authorized users, other cloud users, unauthorized users, or external malicious entities. Encryption of data on client side is one of the solutions to preserve data privacy in the cloud; however, encryption methods are complex and expensive for mobile devices to encrypt and decrypt each file, such as smart phones. We propose a novel light-weight data privacy method (DPM) by using a chaos system for mobile cloud users to store data on multiple clouds. The proposed method enables mobile users to store data in the clouds while it preserves users’ data privacy.

We consider different technologies to deploy our proposed data privacy preservation method on DCCSOA, including the mobile devices, the Internet-of-things (IoT), and Graphic Processing Unit (GPU)-based computing. We also consider different use case scenarios for the proof of concept, including data privacy preservation for users’ photos in smart phones, sensitive electronic health records protection in the cloud, and data privacy preservation for cloud-based databases.

We evaluate both the proposed dynamic architecture and the proposed data privacy preservation method. Our experimental results show that on the one hand DCCSOA enhances standardization by offering a flexible cloud architecture and minimizing the modification on the native cloud services; on the other hand, DPM achieves a superior performance over regular encryption methods in regard to computation time.