Detail publikace

Semi-supervised deep learning approach to break common CAPTCHAs

BOŠTÍK, O. HORÁK, K. KRATOCHVÍLA, L. ZEMČÍK, T. BILÍK, Š.

Originální název

Semi-supervised deep learning approach to break common CAPTCHAs

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

Manual data annotation is a time consuming activity. A novel strategy for automatic training of the CAPTCHA breaking system with no manual dataset creation is presented in this paper. We demonstrate the feasibility of the attack against a text-based CAPTCHA scheme utilizing similar network infrastructure used for Denial of Service attacks. The main goal of our research is to present a possible vulnerability in CAPTCHA systems when combining the brute-force attack with transfer learning. The classification step utilizes a simple convolutional neural network with 15 layers. Training stage uses automatically prepared dataset created without any human intervention and transfer learning for fine-tuning the deep neural network classifier. The designed system for breaking text-based CAPTCHAs achieved 80% classification accuracy after 6 fine-tuning steps for a 5 digit text-based CAPTCHA system. The results presented in this paper suggest, that even the simple attack with a large number of attacking computers can be an effective alternative to current CAPTCHA breaking systems.

Klíčová slova

CAPTCHA;Semi-supervised learning;Convolutional Neural Networks

Autoři

BOŠTÍK, O.; HORÁK, K.; KRATOCHVÍLA, L.; ZEMČÍK, T.; BILÍK, Š.

Vydáno

12. 4. 2021

Nakladatel

Springer

Místo

London

ISSN

0941-0643

Periodikum

NEURAL COMPUTING & APPLICATIONS

Ročník

33

Číslo

20

Stát

Spojené království Velké Británie a Severního Irska

Strany od

13333

Strany do

13343

Strany počet

11

URL

https://link.springer.com/article/10.1007%2Fs00521-021-05957-0

Plný text v Digitální knihovně

http://hdl.handle.net/11012/203005

BibTex

@article{BUT170906,
  author="Ondřej {Boštík} and Karel {Horák} and Lukáš {Kratochvíla} and Tomáš {Zemčík} and Šimon {Bilík}",
  title="Semi-supervised deep learning approach to break common CAPTCHAs",
  journal="NEURAL COMPUTING & APPLICATIONS",
  year="2021",
  volume="33",
  number="20",
  pages="13333--13343",
  doi="10.1007/s00521-021-05957-0",
  issn="0941-0643",
  url="https://link.springer.com/article/10.1007%2Fs00521-021-05957-0"
}