The make-up tips by Russian security expert Grigori Bakunov show how hopeless the fight against omnipresent surveillance via face recognition cameras actually is. Anyone who has to protect himself so conspicuously against his identification need hardly worry about attentive looks. Also in this country is tracked digitally and offline via face recognition.

Russian IT security expert Grigori Bakunov has developed an algorithm to create specific make-up patterns. The stripes and dots distributed on the human face are intended to cancel the detection mechanisms of surveillance cameras and prevent the face recognition of the systems.

Bakunov, who works for the Russian Google competitor Yandex, keeps attracting attention with his contributions to security issues. Last year, for example, he played “Pokémon Go” and discovered that the GPS systems of smartphones near the Russian Kremlin were misleading.

According to Grigori Bakunov, the driving force for the development of the algorithms was that in his hometown of Moscow there is now an increasing number of omnipresent surveillance cameras that could theoretically trace every single one of his paths down to the smallest detail. In Germany, too, the investigative authorities are experimenting with camera systems that explicitly rely on facial recognition. For example, the Federal Police in Berlin distribute Amazon vouchers to guinea pigs who volunteer to monitor regularly in a specific area.

Also in the countermeasures one shows in the programmer and artist scene so far ingeniously. While Bakunov focuses on the eye-catching stripes, dots and geometric patterns on his face, New York artist Adam Harvey developed a printable pattern with many stylized faces . The motif could be printed on a shirt, for example, to completely confuse the existing surveillance cameras.

Originally, Grigori Bakunov planned to incorporate the algorithm into a website, so that anyone could personally generate make-up tips of a special kind. However, according to own data the developer put this intention back provisionally, because the misuse potential of the system is high. In addition to the face recognition of surveillance cameras, for example, the camera systems of banks should come through the pattern completely out of step. Accordingly, criminals could exploit his software.

The previous approaches to the Überlistung of the cameras actually show how mature the systems are already, because to their Aushebung you have to draw attention to a counterproductive conspicuous way on itself. Anyone who puts on such a wildly patterned shirt or runs Mohawk-style make-up through Moscow, has to worry about surveillance cameras actually the slightest worry.

The question is whether the algorithms can also outsmart the facial recognition systems of Facebook & Co. The Social Network has been relying on an appropriate system for quite some time to analyze relationships between people through images. And the advertising industry has long since discovered the technology for themselves: Digital billboards in shopping centers, at railway stations or in the city center should be able to follow a person’s shopping path “offline” via their integrated cameras.

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The make-up tips by Russian security expert Grigori Bakunov show how hopeless the fight against omnipresent surveillance via face recognition cameras actually is. Anyone who has to protect himself so conspicuously against his identification need hardly worry about attentive looks. Also in this country is tracked digitally and offline...