Statistically regulating program behavior via mainstream computing

  • Authors:

  • Mark William Stephenson;Ram Rangan;Emmanuel Yashchin;Eric Van Hensbergen

  • Affiliations:

  • International Business Machines, Austin, TX, USA;NVIDIA, Austin, TX, USA;International Business Machines, Yorktown Heights, NY, USA;International Business Machines, Austin, TX, USA

  • Venue:
  • Proceedings of the 8th annual IEEE/ACM international symposium on Code generation and optimization
  • Year:
  • 2010

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Abstract

We introduce mainstream computing, a collaborative system that dynamically checks a program--via runtime assertion checks--to ensure that it is running according to expectation. Rather than enforcing strict, statically-defined assertions, our system allows users to run with a set of assertions that are statistically guaranteed to fail at a rate bounded by a user-defined probability, pfail. For example, a user can request a set of assertions that will fail at most 0.5% of the times the application is invoked. Users who believe their usage of an application is mainstream can use relatively large settings for pfail. Higher values of pfail provide stricter regulation of the application which likely enhances security, but will also inhibit some legitimate program behaviors; in contrast, program behavior is unregulated when pfail = 0, leaving the user vulnerable to attack. We show that our prototype is able to detect denial of service attacks, integer overflows, frees of uninitialized memory, boundary violations, and an injection attack. In addition we perform experiments with a mainstream computing system designed to protect against soft errors.