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http://dx.doi.org/10.13089/JKIISC.2013.23.5.909

Analysis of Naver CAPTCHA with Effective Segmentation  

Nyang, Dae Hun (인하대학교 컴퓨터정보공학과)
Choi, Yong Heon (인하대학교 컴퓨터정보공학과)
Hong, Seok Jun (인하대학교 정보통신공학과)
Lee, Kyunghee (수원대학교 전기공학과)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.23, no.5, 2013 , pp. 909-917 More about this Journal
Abstract
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.
Keywords
CAPTCHA; Breaking CAPTCHA; SVM; Character Separation;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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