Researchers have taught a neural network to deceive facial recognition systems that are installed in public
The new development defines those parts of the facewhich are most often read by the face recognition system, then it selects a special make-up that will help deceive the system. Then this makeup is applied to a person: as a result, the accuracy of the face recognition system decreases from 47.5% to 1.2%
The neural network works in several stages and works with two models for face recognition:
- own (it is also called surrogate).
- target (to be fooled).
First, the algorithm reads several photosperson and random people of the same sex. The algorithm then creates a heat map that shows the main areas that are the hallmarks of a particular person.
Next, a new face with makeup is created based on the heatmap. He is again passed through the recognition system until it ceases to recognize the person. After that, the resulting makeup can be applied.
The authors note that their development not only deceives recognition systems, but is also invisible to people, since the makeup is normal and does not stand out from the crowd.
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