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Book Summary:
Modern distributed applications are long-lived, are expected to provide flexible and adaptive data services, and must meet the functionality and scalability challenges posed by dynamically changing user communities in heterogeneous execution environments. The practical implications of these requirements are that reconfiguration and upgrades are increasingly necessary, but opportunities to perform such tasks offline are greatly reduced. Developers are responding to this situation by dynamically extending or adjusting application functionality and by tuning application performance, a typical method being the incorporation of client- or context-specific code into applications\' execution loops. Our work addresses a basic roadblock in deploying such solutions: the protection of key application components and sensitive data in distributed applications. Our approach, termed Dynamic Differential Data Protection (D3P), provides fine-grain methods for providing component-based protection in distributed applications. Context-sensitive, application-specific security methods are deployed at runtime to enforce restrictions in data access and manipulation. D3P is suitable for low- or zero-downtime environments, since deployments are performed while applications run. D3P is appropriate for high performance environments and for highly scalable applications like publish/subscribe, because it creates native codes via dynamic binary code generation. Finally, due to its integration into middleware, D3P can run across a wide variety of operating system and machine platforms. This dissertation introduces D3P, using sample applications from the high performance and pervasive computing domains to illustrate the problems addressed by our D3P solution. It also describes how D3P can be integrated into modern middleware. We present experimental evaluations which demonstrate the fine-grain nature of D3P, that is, its ability to capture individual end users\' or components\' needs for data protection, and also describe the performance implications of using D3P in data-intensive applications. |
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