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TRAILS: Efficient data flow tracking through hw-assisted parallelization

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Stevens Institute of Technology Hoboken United States

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The goal of this effort is to make currently opaque computing systems transparent by providing high-fidelity visibility into component interactions during system operation at the hardware architecture layer, while imposing minimal performance overhead. The scope of this effort is to develop a novel architecture for efficiently performing dynamic data-flow tracking through hardware-assisted parallelization. The goal includes the creation of an execution environment that provides low-overhead, fine-grained, data-flow tracking DFT as a utility for security, privacy, and other applications. Trails aims to exploit the parallelism available in modern architectures to improve DFT performance without the demand for more resources than the ones already required to apply it in line with the application.

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Technical Report,28 Sep 2016,30 Jun 2019



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Approved For Public Release;

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