DocumentCode :
630422
Title :
Anti-SIFT Images Based CAPTCHA Using Versatile Characters
Author :
Chen-Chiung Hsieh ; Zong-Yu Wu
Author_Institution :
Dept. of Comput. Sci. & Eng., Tatung Univ., Taipei, Taiwan
fYear :
2013
fDate :
24-26 June 2013
Firstpage :
1
Lastpage :
4
Abstract :
Due to vigorous development of pattern recognition, traditional human form filling tasks would be replaced by automated processes. However, these automation processes are often misused for illegal behavior such as spam e-mail or application for website account. In order to prevent website owner from suffering the attacks of automated program, this paper proposed an innovative image-based CAPTCHA for distinguishing human and computer by embedding versatile characters in the images. The proposed method makes the characters indiscernible by automated image analysis technologies like scale-invariant feature transform while human can easily distinguish the location of the embedded characters. Our designed mechanism was capable to elude such kind of attacks. In experiments, 15 users were invited to test the system and the success rate is 86%. If wrong operations like clicking out of text boxes were excluded, the success rate reached 95%. Compare the average logging time with reCAPTCHA and HELLO CAPTCHA, the proposed method is faster than these two methods by 32 seconds and 115 seconds, respectively.
Keywords :
feature extraction; image coding; security of data; transforms; HELLO CAPTCHA; Website account; antiSIFT image based CAPTCHA; automated image analysis technologies; automated program attacks; automation processes; average logging time; human form filling tasks; illegal behavior; innovative image-based CAPTCHA; pattern recognition; reCAPTCHA; scale-invariant feature transform; spam e-mail; text boxes; versatile characters; CAPTCHAs; Computers; Feature extraction; Image color analysis; Man machine systems; Switches; Transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Applications (ICISA), 2013 International Conference on
Conference_Location :
Suwon
Print_ISBN :
978-1-4799-0602-4
Type :
conf
DOI :
10.1109/ICISA.2013.6579426
Filename :
6579426
Link To Document :
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