A Novel Image Based CAPTCHA Using Jigsaw Puzzle

Most commonly used CAPTCHAs are text-based CAPTCHAs which relay on the distortion of texts in the background image. With the development of automated computer vision techniques, which have been designed to remove noise and segment the distorted strings to make characters readable for OCR, traditional text-based CAPTHCAs are not considered safe anymore for authentication. A novel image based CAPTCHA which involves in solving a jigsaw puzzle is presented in this paper. An image is divided into an n¡Án (n=3, 4 or 5, depends on security level) pieces to construct the jigsaw puzzle CAPTCHA. Only two of the pieces are misplaced from their original positions. Users are required to find the two pieces and swap them. Considering the previous works which are devoted to solving jigsaw puzzles using edge matching technique, the edges of all pieces are processed with glitch treatment to prevent the computer automatic solving. Experiments and security analysis proved that human users can complete the CAPTCHA verification quickly and accurately, but computers rarely can. It is a promising substitution to the current text-based CAPTCHA.

[1]  Ashish Jain,et al.  Sequenced Tagged Captcha: Generation and its Analysis , 2009, 2009 IEEE International Advance Computing Conference.

[2]  Jeffrey P. Bigham,et al.  Evaluating existing audio CAPTCHAs and an interface optimized for non-visual use , 2009, CHI.

[3]  John Langford,et al.  CAPTCHA: Using Hard AI Problems for Security , 2003, EUROCRYPT.

[4]  Margaret M. Fleck,et al.  Jigsaw puzzle solver using shape and color , 1998, ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344).

[5]  John Langford,et al.  Telling humans and computers apart automatically , 2004, CACM.

[6]  Patrice Y. Simard,et al.  Using Machine Learning to Break Visual Human Interaction Proofs (HIPs) , 2004, NIPS.

[7]  Yeuan-Kuen Lee,et al.  A Projection-based Segmentation Algorithm for Breaking MSN and YAHOO CAPTCHAs , 2008 .

[8]  Jon Howell,et al.  Asirra: a CAPTCHA that exploits interest-aligned manual image categorization , 2007, CCS '07.

[9]  Henry S. Baird,et al.  PessimalPrint: a reverse Turing test , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[10]  Rich Gossweiler,et al.  WWW 2009 MADRID! Track: User Interfaces and Mobile Web / Session: User Interfaces What’s Up CAPTCHA? A CAPTCHA Based on Image Orientation , 2022 .

[11]  Fenghui Yao,et al.  A shape and image merging technique to solve jigsaw puzzles , 2003, Pattern Recognit. Lett..

[12]  Philippe Golle,et al.  Machine learning attacks against the Asirra CAPTCHA , 2008, CCS.

[13]  Henry S. Baird,et al.  BaffleText: a Human Interactive Proof , 2003, IS&T/SPIE Electronic Imaging.

[14]  Klaus Hansen,et al.  Solving jigsaw puzzles using image features , 2008, Pattern Recognit. Lett..

[16]  Tarak Gandhi,et al.  An automatic jigsaw puzzle solver , 1994, Proceedings of 12th International Conference on Pattern Recognition.