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 is formulating 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 a grading of the severity of the infractions. Our ongoing work on stochastic computing is being leveraged to provide a foundation for the framework.
Naresh Shanbhag and Rakesh Kumar
Secure Platforms via Stochastic Computing