STRATEGY AND ALGORITHMS FOR DETECTING VULNERABILITIES IN SOFTWARE MODELS OF HARDWARE

Abstract

Technologies of integrated circuits are constantly developing. There is a trend of many computing devices becoming widely available to the public, stimulating curiosity and innovation for many through the rapid creation, deployment, or even operation of hardware systems. Similarly, technology and their capabilities have also grown significantly over the decades. However, as technology continued to develop, so did the abundance of information that became readily available to almost everyone around the world. As a result, it has become possible for many people without prior knowledge or experience to adequately acquire the skills needed to design and implement hardware systems that can enhance or utilize everyday technology. Although the devices that facilitate this Internet of Things have been aimed at improving the quality of life and contributing to the smart home revolution, they have become a common target for many hardware hackers. The work solves just such a problem regarding the impossibility of entering or detecting third-party signs in software models of hardware.

The developed strategy and tools, which are based on the presented generalized algorithms, are the basis of the method for protecting software models of hardware. The basis of the developed strategy is an improved genetic algorithm. The strategy-based ciphertext protection method includes dynamic controlled permutations that produce changes to ensure that the output during the next round does not contain one-time changes and the classical attack methodology cannot be implemented.

The direction of further research is the improvement of sets of models of third-party signs for their further use in the study of software models of hardware.