Secure Platforms via Stochastic Computing
The criticality of the information protection and assurance (IPA) problem has understandably sparked rich intellectual and material investment into finding a solution. Several efforts have centered on understanding, identifying, tolerating, and patching security vulnerabilities at different levels of the electronic system stack for various security attack models. Most of these approaches tend to fall into the “sand-boxing” category, whereby unusual events are sequestered until their potential impacts are identified. Such efforts tend to be directed at well-known threats, and thus require that all existing techniques be revisited as newer attack models emerge.
This project formulated a framework for designing secure computing platforms that treat security infractions as computational errors and employ error-resiliency techniques to tolerate them, while simultaneously providing the user with alert levels based on grading of the severity of the infractions. Our work on stochastic computing has been leveraged to provide a foundation for the framework.
Hard Problem Addressed
- Resilient Architectures
- Joseph Sloan, Rakesh Kumar, and Greg Bronevetsky, “An Algorithmic Approach to Error Localization and Partial Recomputation for Low-Overhead Fault Tolerance”, 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2013), Budapest, Hungary, June 24-27, 2013. [full text]
- Biplab Deka, Alex A. Birklykke, Henry Duwe, Vikash K. Mansighka, and Rakesh Kumar, “Markov Chain Algorithms: A Template for Building Future Robust Low-power Systems”, Philosophical Transactions of the Royal Society A Mathematical, Physical and Engineering Sciences, June 28, 2014. [full text]