Development of two novel face-recognition CAPTCHAs: A security and usability study

Keywords

it-security, student-paper

Summary

CAPTCHAs are challenge-response tests that aim at preventing unwanted machines, including bots, from accessing web services while providing easy access for humans. Recent advances in artificial-intelligence based attacks show that the level of security provided by many state-of-the-art text-based CAPTCHAs is declining. At the same time, techniques for distorting and obscuring the text, which are used to maintain the level of security, make text-based CAPTCHAs difficult to solve for humans, and thereby further degrade usability. The need for developing alternative types of CAPTCHAs that improve both the current security and the usability levels has been emphasized widely. With this study, we contribute to research through (1) the development of two new face recognition CAPTCHAs (Farett-Gender and Farett-Gender&Age), (2) the security analysis of both procedures, and (3) the provision of empirical evidence that one of the suggested CAPTCHAs (Farett-Gender) is similar to Google’s reCAPTCHA and better than KCAPTCHA concerning effectiveness (error rates), superior to both regarding learnability and satisfaction but not efficiency.

Article / DOI link Author copy

Citation (APA style)

Schryen, G., Wagner, G., & Schlegel, A. (2016). Development of two novel face-recognition CAPTCHAs: A security and usability study. Computers & Security 60, 95–116. https://doi.org/10.1016/J.COSE.2016.03.007

Citation: BibTeX

@article{SchryenWagnerSchlegel2016,
  doi        = {10.1016/J.COSE.2016.03.007},
  author     = {Schryen, Guido and Wagner, Gerit and Schlegel, Alexander},
  journal    = {Computers & Security},
  title      = {Development of two novel face-recognition CAPTCHAs: A security and usability study},
  year       = {2016},
  volume     = {60},
  pages      = {95--116},
  url        = {https://www.sciencedirect.com/science/article/pii/S0167404816300293},
  abstract   = {CAPTCHAs are challenge-response tests that aim at preventing unwanted machines, including bots, from accessing web services while providing easy access for humans. Recent advances in artificial-intelligence based attacks show that the level of security provided by many state-of-the-art text-based CAPTCHAs is declining. At the same time, techniques for distorting and obscuring the text, which are used to maintain the level of security, make text-based CAPTCHAs difficult to solve for humans, and thereby further degrade usability. The need for developing alternative types of CAPTCHAs that improve both the current security and the usability levels has been emphasized widely. With this study, we contribute to research through (1) the development of two new face recognition CAPTCHAs (Farett-Gender and Farett-Gender&Age), (2) the security analysis of both procedures, and (3) the provision of empirical evidence that one of the suggested CAPTCHAs (Farett-Gender) is similar to Google's reCAPTCHA and better than KCAPTCHA concerning effectiveness (error rates), superior to both regarding learnability and satisfaction but not efficiency.}
}

Citation: RIS

TY  - JOUR
AU  - Schryen, Guido
AU  - Wagner, Gerit
AU  - Schlegel, Alexander
TI  - Development of two novel face-recognition CAPTCHAs: A security and usability study
T2  - Computers & Security
PY  - 2016
VL  - 60
SP  - 95
EP  - 116
DO  - 10.1016/J.COSE.2016.03.007
UR  - https://www.sciencedirect.com/science/article/pii/S0167404816300293
ER  -