GrammaTech Lands DARPA AIE Program

January 8, 2021

GrammaTech has been awarded a contract under the Defense Advanced Research Projects Agency (DARPA) AIE program to research the use of AI to infer mathematical algorithms baked into binary applications of cyber physical systems. DARPA AIE sponsors research to prototype the development of new, game-changing AI technologies for U.S. National Security.

“This is the latest in a series of DARPA contracts awarded to GrammaTech based on our expertise in artificial intelligence and machine learning for software development and security,” said Mike Dager, CEO of GrammaTech. “These research projects are all designed to address the challenges of developing or maintaining critical infrastructure software when resources and expertise are scarce, and standards are rapidly evolving.”

GrammaTech is developing ReMath, an AI tool that can automatically infer high-level mathematical representations from existing binaries in cyber-physical systems and embedded software. Currently, subject matter experts (SMEs) must manually analyze binaries through a time-consuming and expensive process, using low-level tools such as disassemblers, debuggers, and decompilers to recover the higher-level constructs encoded in software. This requires extensive reverse engineering to be able to understand and modify systems. ReMath aims to address this gap and dramatically improve productivity by recovering and converting machine language into representations that SMEs find natural to work with.

“ReMath will enable subject matter experts to rapidly understand and model hardware-interfacing computations embedded in cyber-physical system binaries,” said Alexey Loginov, Vice President of Research at GrammaTech. “This research will greatly lower the cost of analyzing, maintaining, and modernizing cyber-physical devices.”

Sample applications for this research include industrial control systems used in power and chemical processing plants where domain experts without reverse-engineering or coding experience could maintain and make changes to existing software.

This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Agreement No. HR00112190018. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of DARPA.

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