Darko Brodić

HC
3papers
20citations
Novelty17%
AI Score14

3 Papers

HCJun 30, 2017
Statistical Analysis of Dice CAPTCHA Usability

Darko Brodić, Alessia Amelio, Ivo R. Draganov

In this paper the elements of the CAPTCHA usability are analyzed. CAPTCHA, as a time progressive element in computer science, has been under constant interest of ordinary, professional as well as the scientific users of the Internet. The analysis is given based on the usability elements of CAPTCHA which are abbreviated as user-centric approach to the CAPTCHA. To demonstrate it, the specific type of Dice CAPTCHA is used in the experiment. The experiment is conducted on 190 Internet users with different demographic characteristics on laptop and tablet computers. The obtained results are statistically processed. At the end, the results are compared and conclusion of their use is drawn.

CVJun 19, 2017
The $\mathcal{E}$-Average Common Submatrix: Approximate Searching in a Restricted Neighborhood

Alessia Amelio, Darko Brodić

This paper introduces a new (dis)similarity measure for 2D arrays, extending the Average Common Submatrix measure. This is accomplished by: (i) considering the frequency of matching patterns, (ii) restricting the pattern matching to a fixed-size neighborhood, and (iii) computing a distance-based approximate matching. This will achieve better performances with low execution time and larger information retrieval.

HCDec 1, 2016
Analysis of the Human-Computer Interaction on the Example of Image-based CAPTCHA by Association Rule Mining

Darko Brodić, Alessia Amelio

The paper analyzes the interaction between humans and computers in terms of response time in solving the image-based CAPTCHA. In particular, the analysis focuses on the attitude of the different Internet users in easily solving four different types of image-based CAPTCHAs which include facial expressions like: animated character, old woman, surprised face, worried face. To pursue this goal, an experiment is realized involving 100 Internet users in solving the four types of CAPTCHAs, differentiated by age, Internet experience, and education level. The response times are collected for each user. Then, association rules are extracted from user data, for evaluating the dependence of the response time in solving the CAPTCHA from age, education level and experience in internet usage by statistical analysis. The results implicitly capture the users' psychological states showing in what states the users are more sensible. It reveals to be a novelty and a meaningful analysis in the state-of-the-art.