A self-adaptive algorithm to defeat text-based CAPTCHA Conference Paper

abstract

• 2016 IEEE. CAPTCHA (Completely Automated Public Turing test to Tell Computers and Humans Apart) is almost everywhere in data entry due to automated scripts like bots. Nowadays, text-based scheme is still applied most widely, which typically need the users to answer questions regarding recognition task. In particular, the segmentations of different types of CAPTCHAs are not always the same. As so far, there isn't any universal way to solve the segmentation problems. In this paper, we present a novel adaptive algorithm and based on that we create a system to defeat several CAPTCHAs at the same time. The CAPTCHA datasets we used are from the State Administration for Industry & Commerce of the People's Republic of China. There are totally 33 entrances of CAPTCHAs we need to solve. In this experiments, we assume that each of the entrance is known. Results are provided showing how our algorithms work well towards these CAPTCHAs.

name of conference

• 2016 IEEE International Conference on Industrial Technology (ICIT)

authors

• Lu, Mi

published proceedings

• PROCEEDINGS 2016 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT)

author list (cited authors)

• Wang, Y. e., & Lu, M. i.

citation count

• 8

complete list of authors

• Wang, Ye||Lu, Mi

publication date

• March 2016

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

• Affine Transformation
• Captcha
• Clustering
• Recognition
• Reverse Turing Test
• Segmentation

Digital Object Identifier (DOI)

• 10.1109/icit.2016.7474839

International Standard Book Number (ISBN) 13

• 9781467380751

start page

• 720

end page

• 725

volume

• 2016-May

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Ficit.2016.7474839