More Web Proxy on the site http://driver.im/

research-article

Balancing usability and security in a video CAPTCHA

Authors:

Kurt Alfred Kluever,

Richard ZanibbiAuthors Info & Claims

SOUPS '09: Proceedings of the 5th Symposium on Usable Privacy and Security

Article No.: 14, Pages 1 - 11

https://doi.org/10.1145/1572532.1572551

Published: 15 July 2009 Publication History

Abstract

We present a technique for using content-based video labeling as a CAPTCHA task. Our CAPTCHAs are generated from YouTube videos, which contain labels (tags) supplied by the person that uploaded the video. They are graded using a video's tags, as well as tags from related videos. In a user study involving 184 participants, we were able to increase the human success rate on our video CAPTCHA from roughly 70% to 90%, while keeping the success rate of a tag frequency-based attack fixed at around 13%. Through a different parameterization of the challenge generation and grading algorithms, we were able to reduce the success rate of the same attack to 2%, while still increasing the human success rate from 70% to 75%. The usability and security of our video CAPTCHA appears to be comparable to existing CAPTCHAs, and a majority of participants (60%) indicated that they found the video CAPTCHAs more enjoyable than traditional CAPTCHAs in which distorted text must be transcribed.

References

[1]

H. S. Baird and K. Popat. Human Interactive Proofs and Document Image Analysis. In Proc. IAPR DAS 2002, ACM Press (2002), 507--518.

Digital Library

[2]

M. Cha, H. Kwak, P. Rodriguez, Y.-Y. Ahn, and S. Moon. I Tube, You Tube, Everybody Tubes: Analyzing the World's Largest User Generated Content Video System. In Proc. IMC 2007, ACM Press (2007), 1--14.

Digital Library

[3]

K. Chellapilla, K. Larson, P. Y. Simard, and M. Czerwinski. Building Segmentation Based Human-friendly Human Interaction Proofs (HIPs). In Proc. HIP 2005, LNCS (2005), 1--26.

Digital Library

[4]

M. Chew and H. S. Baird. Baffletext: A Human Interactive Proof. In Proc. DRR 2003, IST/SPIE (2003), 305--316.

[5]

M. Chew and J. D. Tygar. Image Recognition CAPTCHAs. In Proc. ISC 2004, LNCS (2004), 268--279.

[6]

J. Douceur, J. Elson, J. Howell, and J. Saul. Asirra: A CAPTCHA that Exploits Interest-Aligned Manual Image Categorization. In Proc. CCS 2007, ACM Press (2007), 366--374.

Digital Library

[7]

G. Geisler and S. Burns. Tagging Video: Conventions and Strategies of the YouTube Community. In Proc. JCDL 2007, ACM/IEEE (2007), 480--480.

Digital Library

[8]

P. B. Godfrey Text-based CAPTCHA algorithms. In Proc. HIP 2002.

[9]

P. Golle. Machine Learning Attacks Against the ASIRRA CAPTCHA. In Proc. CCS 2008, ACM Press (2008), 535--542.

Digital Library

[10]

L. A. Goodman. Snowball sampling. The Annals of Mathematical Statistics 32, 1 (1961), 148--170.

[11]

R. Gossweiler, M. Kamvar and S. Baluja. What's Up CAPTCHA? A CAPTCHA Based on Image Orientation. In Proc. WWW 2009, ACM Press (2009), 841--850.

Digital Library

[12]

M. J. Halvey and M. T. Keane. Analysis of Online Video Search and Sharing. In Proc. Hypertext 2007, ACM Press (2007), 217--226.

Digital Library

[13]

G. W. Hart. To Decode Short Cryptograms. Communications of the ACM 37, 9 (1994), 102--108.

Digital Library

[14]

A. Kerckhoffs. La Cryptographie Militaire. Journal des Sciences Militaires 9, (1883), 161--191.

[15]

K. A. Kluever. Evaluating the Usability and Security of a Video CAPTCHA. Master's thesis, Rochester Institute of Technology, 2008.

[16]

G. Kochanski, D. P. Lopresti and C. Shih. Using a Text-to-Speech Synthesizer to Generate a Reverse Turing Test. In Proc. ICTAI 2003, IEEE Press (2003), 226--232.

Digital Library

[17]

V. I. Levenshtein. Binary Codes Capable of Correcting Deletions, Insertions, and Reversals. Soviet Physics Doklady 10, (1966), 707--710.

[18]

J. B. Lovins. Development of a Stemming Algorithm. Mechanical Translation and Computational Linguistics 11, (1968), 22--31.

[19]

M. Naor. Verification of a human in the loop or Identification via the Turing Test. Unpublished manuscript, (1996).

[20]

J. C. Paolillo. Structure and Network in the YouTube Core. In Proc. HICSS 2008, IEEE Press (2008), 156--166.

Digital Library

[21]

M. F. Porter. An Algorithm for Suffix Stripping. Program 14, 3 (1980), 130--137.

[22]

Y. Rui and Z. Liu. ARTiFACIAL: Automated Reverse Turing test using FACIAL features. Multimedia Systems Journal 9, 6 (2004), 493--502.

Digital Library

[23]

A. Rusu. Exploiting the Gap in Human and Machine Abilities in Handwriting Recognition for Web Security Applications. PhD thesis, University of New York at Buffalo, 2007.

Digital Library

[24]

A. M. Turing. Computing Machinery and Intelligence. Mind 59, 236 (1950), 433--460.

[25]

C. van Rijsbergen. Information Retrieval, Second edition. Butterworth-Heinemann Ltd, London, UK, 1979.

Digital Library

[26]

L. von Ahn, M. Blum, and J. Langford. Telling Humans and Computers Apart Automatically. Communications of the ACM 47, 2 (2004), 56--60.

Digital Library

[27]

L. von Ahn and L. Dabbish. Labeling Images with a Computer Game. In Proc. CHI 2004, ACM Press (2004), 319--326.

Digital Library

[28]

J. Yan and A. S. E. Ahmad. A Low-cost Attack on a Microsoft CAPTCHA. In Proc. CCS 2008, ACM Press (2008), 543--554.

Digital Library

[29]

J. Yan and A. S. E. Ahmad. Usability of CAPTCHAs or usability issues in CAPTCHA design. In Proc. SOUPS 2008, ACM Press (2008), 44--52.

Digital Library

Cited By

Zhao RDeng XWang YYan ZHan ZChen LXue ZWang Y(2023)GeeSolver: A Generic, Efficient, and Effortless Solver with Self-Supervised Learning for Breaking Text Captchas2023 IEEE Symposium on Security and Privacy (SP)10.1109/SP46215.2023.10179379(1649-1666)Online publication date: May-2023
https://doi.org/10.1109/SP46215.2023.10179379
Kumar MJindal MKumar M(2023)An efficient technique for breaking of coloured Hindi CAPTCHASoft Computing10.1007/s00500-023-07844-327:16(11661-11686)Online publication date: 25-Jan-2023
https://doi.org/10.1007/s00500-023-07844-3
Shi CXu XJi SBu KChen JBeyah RWang T(2022)Adversarial CAPTCHAsIEEE Transactions on Cybernetics10.1109/TCYB.2021.307139552:7(6095-6108)Online publication date: Jul-2022
https://doi.org/10.1109/TCYB.2021.3071395
Show More Cited By

Index Terms

Balancing usability and security in a video CAPTCHA
1. Human-centered computing
  1. Human computer interaction (HCI)
2. Security and privacy
  1. Systems security
    1. Operating systems security

Recommendations

CAPTCHA: Impact of Website Security on User Experience
ICIIT '19: Proceedings of the 2019 4th International Conference on Intelligent Information Technology

As currently many people use the Internet to access websites, Internet security becomes an important topic. One popular security mechanism is Captcha or Completely Automated Public Turing Computer and Humans Apart, which determine whether or not the ...
Image enhanced CAPTCHA for web security
CISR '14: Proceedings of the 9th Annual Cyber and Information Security Research Conference

Many websites use CAPTCHA to defend against malicious automated programs from performing abusive tasks such as illegitimate account registration. CAPTCHA is widely used on commercial websites as a HIP system due to its simplicity of use and ...
Automatic tag expansion using visual similarity for photo sharing websites

In this paper we present an automatic photo tag expansion method designed for photo sharing websites. The purpose of the method is to suggest tags that are relevant to the visual content of a given photo at upload time. Both textual and visual cues are ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

SOUPS '09: Proceedings of the 5th Symposium on Usable Privacy and Security

July 2009

205 pages

ISBN:9781605587363

DOI:10.1145/1572532

General Chair:
Lorrie Faith Cranor
Carnegie Mellon University

Copyright © 2009 Copyright held by the author/owner.

Sponsors

Carnegie Mellon CyLab
Google Inc.

In-Cooperation

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 July 2009

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

SOUPS '09

Sponsor:

SOUPS '09: Symposium on Usable Privacy and Security

July 15 - 17, 2009

California, Mountain View, USA

Acceptance Rates

SOUPS '09 Paper Acceptance Rate 15 of 49 submissions, 31%;

Overall Acceptance Rate 15 of 49 submissions, 31%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

58
Total Citations
View Citations
788
Total Downloads

Downloads (Last 12 months)25
Downloads (Last 6 weeks)3

Reflects downloads up to 15 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Zhao RDeng XWang YYan ZHan ZChen LXue ZWang Y(2023)GeeSolver: A Generic, Efficient, and Effortless Solver with Self-Supervised Learning for Breaking Text Captchas2023 IEEE Symposium on Security and Privacy (SP)10.1109/SP46215.2023.10179379(1649-1666)Online publication date: May-2023
https://doi.org/10.1109/SP46215.2023.10179379
Kumar MJindal MKumar M(2023)An efficient technique for breaking of coloured Hindi CAPTCHASoft Computing10.1007/s00500-023-07844-327:16(11661-11686)Online publication date: 25-Jan-2023
https://doi.org/10.1007/s00500-023-07844-3
Shi CXu XJi SBu KChen JBeyah RWang T(2022)Adversarial CAPTCHAsIEEE Transactions on Cybernetics10.1109/TCYB.2021.307139552:7(6095-6108)Online publication date: Jul-2022
https://doi.org/10.1109/TCYB.2021.3071395
Pritom AAl Mashuk MAhmed SMonira NIslam M(2022)GESTCHA: a gesture-based CAPTCHA design for smart devices using angular velocityMultimedia Tools and Applications10.1007/s11042-022-13272-682:1(521-549)Online publication date: 7-Jun-2022
https://doi.org/10.1007/s11042-022-13272-6
Tian PLiao WKimbrough TBlasch EYu W(2022)Generating Adversarial Robust Defensive CAPTCHA (GARD-CAPTCHA) in Convolutional Neural NetworksSoftware Engineering Research, Management and Applications10.1007/978-3-031-09145-2_2(17-31)Online publication date: 22-Sep-2022
https://doi.org/10.1007/978-3-031-09145-2_2
Guerar MVerderame LMigliardi MPalmieri FMerlo A(2021)Gotta CAPTCHA ’Em All: A Survey of 20 Years of the Human-or-computer DilemmaACM Computing Surveys10.1145/347714254:9(1-33)Online publication date: 8-Oct-2021
https://dl.acm.org/doi/10.1145/3477142
Kumar MJindal MKumar M(2021)A Systematic Survey on CAPTCHA Recognition: Types, Creation and Breaking TechniquesArchives of Computational Methods in Engineering10.1007/s11831-021-09608-429:2(1107-1136)Online publication date: 14-Jun-2021
https://doi.org/10.1007/s11831-021-09608-4
Asani ELonge OBalla AOgundokun RAdeniyi E(2020)Secure Human-Computer InteractionHandbook of Research on the Role of Human Factors in IT Project Management10.4018/978-1-7998-1279-1.ch010(149-163)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-1279-1.ch010
Feng YCao QQi HRuoti S(2020)SenCAPTCHAProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33973124:2(1-26)Online publication date: 15-Jun-2020
https://dl.acm.org/doi/10.1145/3397312
Shishkin ABezzubtseva AFedorova VDrutsa AGusev GCaverlee JHu XLalmas MWang W(2020)Text Recognition Using Anonymous CAPTCHA AnswersProceedings of the 13th International Conference on Web Search and Data Mining10.1145/3336191.3371795(537-545)Online publication date: 20-Jan-2020
https://dl.acm.org/doi/10.1145/3336191.3371795
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents