• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1011-1019
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• 2015

CAPTCHA(Completely Automated Public Turing test to tell Computers and Humans Apart) is a test used in computing to distinguish whether or not the user is computer or human. Many web sites mostly use the character-based CAPTCHA consisting of digits and characters. Recently, with the development of OCR technology, simple character-based CAPTCHA are broken quite easily. As an alternative, many web sites add noise to make it harder for recognition. In this paper, we analyzed the most recent CAPTCHA, which incorporates the addition of the natural images to obfuscate the characters. We proposed an efficient method using support vector machine to separate the characters from the background image and use convolutional neural network to recognize each characters. As a result, 368 out of 1000 CAPTCHAs were correctly identified, it was demonstrated that the current CAPTCHA is not safe.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.5
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• pp.909-917
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• 2013

CAPTCHA is an automated test to tell apart computers from human mainly for web services, and it has been evolved since the most naive form in which users are requested to input simple strings has been introduced. Though many types of CAPTCHAs have been proposed, text-based CAPTCHAs have been widely prevailed for user convenience. In this paper, we introduce new segmentation schemes and show an attack method to break the CAPTCHA of Naver that occupies more than 70% of the market share in search engine. The experimental results show that 938 trials out of 1000 have successfully analyzed, which implies that we cannot use the CAPTCHA anymore.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.105-112
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• 2009

Nowadays, completely automated public turing tests to tell computers and humans apart(CAPTCHAs) are widely used to prevent various attacks by automated software agents such as creating accounts, advertising, sending spam mails, and so on. In early CAPTCHAs, the characters were simply distorted, so that users could easily recognize the characters. From that reason, using various techniques such as image processing, artificial intelligence, etc., one could easily break many CAPTCHAs, either. As an alternative, By adding noise to CAPTCHAs and distorting the characters in CAPTCHAs, it made the attacks to CAPTCHA more difficult. Naturally, it also made users more difficult to read the characters in CAPTCHAs. To improve the readability of CAPTCHAs, some CAPTCHAs used different colors for the characters. However, the usage of the different colors gives advantages to the adversary who wants to break CAPTCHAs. In this paper, we suggest a method of increasing the recognition ratio of CAPTCHAs based on colors.