Analysis reveals vulnerabilities in synchronized artificial neural networks, suggesting enhanced security measures are needed.
The vulnerability of the technology for generating a common cryptographic key using synchronized artificial neural networks (ANN) is considered in a relatively new type of attack called two-way. The essence of the attack is that a cryptanalyst, listening to an open communication channel, creates two identical artificial neural networks, one of which he synchronizes with the network of one of the legal subscribers, and the second with the network of another legal subscriber. By comparing the vectors of weight coefficients of attacking networks, the cryptanalyst is able to determine the moment of full synchronization of the networks of legal subscribers and the value of the generated secret number. Next, we examine the possibilities of a two-way attack using various models of secret number generation.
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Holikau et al. (2025) studied this question.
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