The algebraic approach in cybersecurity was demanded over the past two decades with the appearance of efficient solving and deductive tools. Different techniques like symbolic modeling and concolic computations use the algebraic approach that has created more possibilities for methods of detection in cybersecurity.

The Defense Advanced Research Projects Agency (DARPA) launched the Cyber Grand Challenge to create defensive systems with purposes of automated, scalable, machine-speed detection of vulnerabilities and cyber infections. In 2016, there were three winners that used the symbolic modeling technique in detection algorithms, which gives the possibility to provide a more efficient implementation of program paths traversal.

Our tools anticipate algebraic matching in different modes. The following applications are available and are under active research:

Algebraic methods of vulnerability detection in binary code

Detection of intruder behavior in a desktop computer, network or cloud

Algebraic fuzzing

Combining machine learning and algebraic approach in fraud detection (presentation)

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