caa a22 4500 605447225 CHVBK 20210128100131.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s11042-013-1823-z doi (NATIONALLICENCE)springer-10.1007/s11042-013-1823-z Li Qiujie College of Mechanical and Electronic Engineering, Nanjing Forestry University, 210037, Nanjing, China aut A computer vision attack on the ARTiFACIAL CAPTCHA [Elektronische Daten] [Qiujie Li] Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) is a reverse Turing test that is used to differentiate bots from humans. Text CAPTCHAs have been widely used in commercial applications, but most of the text CAPTCHAs have been successfully attacked. An alternative is to develop image CAPTCHAs to replace text CAPTCHAs. ARTiFACIAL (Automated Reverse Turing test using FACIAL features) Rui and Liu (2003) is an image CAPTCHA system based on detecting human face and facial features and claimed to be attack-resistant and user-friendly. This paper proposes a compute vision attack on ARTiFACIAL. By carefully analyzing the limitations of face and facial feature detectors that ARTiFACIAL exploits, tailor-made attacking algorithm is designed instead of using general face and facial feature detectors directly. When tested with the 800 ARTiFACIAL challenges, the overall success rate of the attacking algorithm is 18.0 %, which is significantly higher than the estimate of 0.0006 % given in Rui and Liu (2003) for computer vision attacks. It takes an average time 1.47s for a PC with 3.2GHz Intel P4 and 2GB memory to pass an ARTiFACIAL test, compared with 14s for a human subject given in Rui and Liu (2003). From the successful attack, useful lessons for guiding the design of image CAPTCHAs are derived to advance the current understanding of the design of image CAPTCHAs and lead to more secure design. Springer Science+Business Media New York, 2013 CAPTCHA nationallicence ARTiFACIAL nationallicence Attack nationallicence Computer vision nationallicence Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/13(2015-07-01), 4583-4597 1380-7501 74:13<4583 2015 74 11042 https://doi.org/10.1007/s11042-013-1823-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-013-1823-z text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Li Qiujie College of Mechanical and Electronic Engineering, Nanjing Forestry University, 210037, Nanjing, China aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/13(2015-07-01), 4583-4597 1380-7501 74:13<4583 2015 74 11042