Paper Info
Title
All About Uncertainties and Traps: Statistical Oracle-based Attacks on a New CAPTCHA Protection Against Oracle Attacks
Abstract
CAPTCHAs are security mechanisms that try to prevent automated abuse of computer services. Many CAPTCHAs have been proposed but most have known security flaws against advanced attacks. In order to avoid a kind of oracle attacks in which the attacker learns about ground truth labels via active interactions with the CAPTCHA service as an oracle, Kwon and Cha proposed a new CAPTCHA scheme that employ uncertainties and trap images to generate adaptive CAPTCHA challenges, which we call “Uncertainty and Trap Strengthened CAPTCHA” (UTS-CAPTCHA) in this paper. Adaptive CAPTCHA challenges are used widely (either explicitly or implicitly) but the role of such adaptive mechanisms in the security of CAPTCHAs has received little attention from researchers.
Year
DOI
Venue
2020
10.1016/j.cose.2020.101758
Computers & Security
Keywords
DocType
Volume
CAPTCHA,Uncertainty,Trap images,Machine learning,Image classification,Oracle attacks,Statistical attacks
Journal
92
ISSN
Citations 
PageRank 
0167-4048
1
0.39
References 
Authors
0
3
Name
Order
Citations
PageRank
Carlos Javier Hernández-Castro172.52
Shujun Li21131116.82
María D. R-Moreno39715.22