DevilTyper

Author:

Ho Chien-Ju1,Wu Chen-Chi2,Chen Kuan-Ta3,Lei Chin-Laung2

Affiliation:

1. University of California, Los Angeles

2. National Taiwan University

3. Institute of Information Science, Academia Sinica

Abstract

CAPTCHA is an effective and widely used solution for preventing computer programs (i.e., bots) from performing automated but often malicious actions, such as registering thousands of free email accounts or posting advertisement on Web blogs. To make CAPTCHAs robust to automatic character recognition techniques, the text in the tests are often distorted, blurred, and obscure. At the same time, those robust tests may prevent genuine users from telling the text easily and thus distribute the cost of crime prevention among all the users. Thus, we are facing a dilemma, that is, a CAPTCHA should be robust enough so that it cannot be broken by programs, but also needs to be easy enough so that users need not to repeatedly take tests because of wrong guesses. In this article, we attempt to resolve the dilemma by proposing a human computation game for quantifying the usability of CAPTCHAs. In our game, DevilTyper, players try to defeat as many devils as possible by solving CAPTCHAs, and player behavior in completing a CAPTCHA is recorded at the same time. Therefore, we can evaluate CAPTCHAs' usability by analyzing collected player inputs. Since DevilTyper provides entertainment itself, we conduct a large-scale study for CAPTCHAs' usability without the resource overhead required by traditional survey-based studies. In addition, we propose a consistent and reliable metric for assessing usability. Our evaluation results show that DevilTyper provides a fun and efficient platform for CAPTCHA designers to assess their CAPTCHA usability and thus improve CAPTCHA design.

Funder

National Science Council Taiwan

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Chinese Character CAPTCHA Recognition and performance estimation via deep neural network;Neurocomputing;2018-05

2. Association rule mining for the usability of the CAPTCHA interfaces: a new study of multimedia systems;Multimedia Systems;2018-03-21

3. An Empirical Pilot Study of CAPTCHA Complexity Using Eye Tracking;Proceedings of the 16th International Conference on Information Integration and Web-based Applications & Services;2014-12-04

4. Trajectory analysis for user verification and recognition;Knowledge-Based Systems;2012-10

5. Script Familiarity and Its Effect on CAPTCHA Usability;International Journal of Web Portals;2012-04

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