How to Mimic Humans, Guide for Computers

0462913 - ÚI 2017 RIV DE eng C - Conference Paper (international conference)
Kopp, M. - Pištora, N. - Holeňa, Martin
How to Mimic Humans, Guide for Computers.
Proceedings ITAT 2016: Information Technologies - Applications and Theory. Aachen & Charleston: Technical University & CreateSpace Independent Publishing Platform, 2016 - (Brejová, B.), s. 110-117. CEUR Workshop Proceedings, V-1649. ISBN 978-1-5370-1674-0. ISSN 1613-0073.
[ITAT 2016. Conference on Theory and Practice of Information Technologies /16./. Tatranské Matliare (SK), 15.09.2016-19.09.2016]
Grant - others:SGS ČVUT(CZ) SGS16/119/OHK3/1T/18
Institutional support: RVO:67985807
Keywords : CAPTCHA * machine learning * network security * optical character recognition * speech recognition
Subject RIV: IN - Informatics, Computer Science
http://ceur-ws.org/Vol-1649/110.pdf

This paper studies reverse Turing tests to tell humans and computers apart. Contrary to classical Turing tests, the judge is not a human but a computer. These tests are often called Completely Automated Public Turing tests to tell Computers and Humans Apart (CAPTCHA). The main purpose of such test is avoiding automated usage of various services, preventing bots from spamming on forums, securing user logins against dictionary or brute force password guessing and many others. During years, a diversity of tests appeared. In this paper, we focused on the two most classical and widespread schemes, which are text-based and audiobased CAPTCHA, and on their use in the Czech internet environment. The goal of this paper is to point out flaws and weak spots of often used solutions and consequent security risks. To this end, we pipelined several relatively easy algorithms like flood fill algorithm and k-nearest neighbours, to overcome CAPTCHA challenges at several web pages, including state administration.
Permanent Link: http://hdl.handle.net/11104/0262260