This thesis presents a new security policy enforcer designed for securing parallel computation on CUDA GPUs. We show how the very features that make a GPGPU desirable have already been utilized in existing exploits, fortifying the need for security protections on a GPGPU. An aspect weaver was designed for CUDA with the goal of utilizing aspect-oriented programming for security policy enforcement. Empirical testing verified the ability of our aspect weaver to enforce various policies. Furthermore, a performance analysis was performed to demonstrate that using this policy enforcer provides no significant performance impact over manual insertion of policy code. Finally, future research goals are presented through a plan of work. We hope that this thesis will provide for long term research goals to guide the field of GPU security.
|Commitee:||Ou, Xinming, Tu, Yicheng|
|School:||University of South Florida|
|Department:||Computer Science and Engineering|
|School Location:||United States -- Florida|
|Source:||MAI 55/05M(E), Masters Abstracts International|
|Subjects:||Computer Engineering, Computer science|
|Keywords:||Cuda, Distributed computing, Enforceability theory, Parallel computing, Programming languages|
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