Anti-SIFT Images Based CAPTCHA Using Versatile Characters
Chen-Chiung Hsieh, Zongyu Wu · 2013
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.