Russia Is Preparing to Board Pirate AI

A New Layer of Security for Vision Models

Russian researchers from the A. N. Gorban Laboratory for AI, Data Analysis and Modeling at Central University have developed a new method for protecting computer‑vision models from unauthorized copying and misuse. Their key breakthrough: the protection system can be embedded into an already‑trained neural network without any retraining — a major advantage over existing watermarking or licensing approaches.

The work was presented at ICCV 2025, earning strong reviews from experts and marking an important contribution to global AI‑security research.

A Hidden Neuron That Detects a Secret Visual Key

At the core of the method is a specially modified “detector neuron” inserted in place of one of the model’s original components. Under normal conditions, it remains completely invisible to users: the model behaves exactly as expected when processing ordinary images.

But once a secret visual key — a small embedded pattern — appears in the input, the neuron activates. This activation confirms the model’s identity and proves ownership of both the model and the generated output. The probability of accidental triggering is extremely low, which makes the solution suitable for industrial and commercial deployment.

Licensing Built Into the Neural Network Itself

The technology also supports a protection mode in which the model processes data correctly only when the same key is present. If the key is missing, the embedded neurons introduce controlled interference, causing the model to behave incorrectly. This acts as a licensing mechanism built directly into the architecture of the neural network, making illicit use effectively pointless.

The protection module can be integrated into any computer‑vision model without adding computational overhead. This opens the door for secure deployment of AI in mobile applications, medical diagnostics, financial technologies and other sensitive domains where trust and control are essential.