New Machine Learning Algorithm to Break Captcha Easy

The GAN (generative-adversial network) based algorithm was developed by scientists from the UK and China
19 December 2018   1572

An algorithm for machine learning has appeared, which bypasses the text captcha easier, faster and more precisely than previous methods: it recognizes it in 0.05 seconds using a desktop PC. The algorithm was developed by scientists from the UK and China, using the GAN - generative-adversial network.

Conventional machine learning algorithms require millions of samples of initial data for learning. Bots that capture captcha images are easy to recognize and block. The learning process itself is demanding of resources.

For the new algorithm, this amount of data is not required, which means that the attacker does not need to collect it. The neural network is undemanding to computing resources and easy to train - this reduces the cost of preparing an attack.

The researchers said that their method with 100% accuracy recognized captcha on sites such as Megaupload, Blizzard and Authorize.NET. On Amazon, PayPal, Yahoo and other resources, accuracy was less, but also high.

Researchers recommend web site owners to use alternative methods of detecting bots. For example, analyze user behavior patterns and device locations or use biometric data.

Scientists from the English Lancaster and Chinese Northwestern and Beijing universities used the Generative Adversarial Network (GAN). This class of AI algorithms is effective in scenarios where there is not a large amount of training data.

GAN is based on two competing neural networks. One generative generates samples by mixing several source ones, and the other discriminative generates attempts to decipher them. Both networks seek to win each other. In the process of joint competitive training, they significantly improve the quality of their work without the need to use a large amount of initial data.

Researchers collected a total of 500 samples from 11 captcha services used on 32 sites from the top 50 in the Alexa ranking. The developers spent only 2 hours on the collection. In the process of learning, more than 200,000 captchas were “synthesized”.

AI to Recognize Text Written by Invisible Keyboard

Developers said they tried to increase the typing speed on the on-screen keyboards
06 August 2019   328

Korean developers have created an algorithm that recognizes text printed on an imaginary keyboard on a touchscreen. Such a “keyboard” is not tied to a specific area on the screen, and the “keys” are not limited to clear squares.

As a result, a person types blindly in a QWERTY layout without thinking about where the keyboard should be and whether it got into the key.

Imaginary Buttons Press CloudsImaginary Buttons Press Clouds

According to the developers, they tried to increase the typing speed on the on-screen keyboards. The on-screen keyboard, unlike the hardware keyboard, does not offer feedback that confirms pressing. There is a risk to miss and not press the desired button. Because of this, people endlessly stare at the screen and eventually print more slowly.

The new algorithm allows you not to worry about this, you can enter text from memory, and the keyboard with 96% accuracy will guess what the person wanted to say. Tests have shown that the average typing speed on an imaginary keyboard is slightly less than on a hardware keyboard: 45 words per minute versus 51.