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   2092

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”.

BNC to Monitor BTC Community's Mood

The system called Twitter Sentiment analyzes over 34M BTC-related Twitter posts each week, using AI to track the mood of the community
22 January 2020   464

Blockchain-based New Zealand-based research firm Brave New Coin (BNC) has unveiled a new system for measuring the mood of the Bitcoin community based on Twitter messages.

According to BNC, the new Twitter Sentiment rating system analyzes over 34 million BTC-related Twitter posts each week. The company uses artificial intelligence (AI) algorithms that look for records containing the words bitcoin, $ BTC and BTC and others.

BNC notes that user sentiment continues to be a “significant” factor in the price and dynamics of digital assets, and a new technique has been developed to track these sentiments. According to the BNC, it took 18 months to launch the Bitcoin Twitter Sentiment. The data obtained is divided into seven categories - Opinion, Technical Information, Inside the Network, Advertising, Bots, Macros and Hacking.

For the week ending January 17, the most common entries were in the Opinion category - their number was 30.42% of all data received. In second place was the category Technical Information, and in third inside the network (includes information on mining and hashrate).

BNC spokeswoman Pierre Ansaldi said that during the first quarter of this year, the company will also launch community sentiment analysis tools for other crypto assets.