Balancing usability and security in a video CAPTCHA

Kluever, Kurt Alfred; Zanibbi, Richard

doi:10.1145/1572532.1572551

Cited by 87 publications

(72 citation statements)

References 26 publications

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“…which shaped characters are present in the image. In the third stage, on the basis of the character shapes recognized the image in divided to get individual characters which are easy to recognize by a computer [1]. And lastly, these individual characters are read using the OCR.…”

Section: Proposed Workmentioning

confidence: 99%

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Towards Solving the Google CAPTCHA

Mehta¹,

Sharma²

2014

IJCA

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CAPTCHA is now a technology which is used all over the internet to protect websites from program bots. One of the major issues which CAPTCHA provides a solution to is, stopping spammers for creating unlimited accounts and sending emails to millions of people spam mails. In this paper, we are proposing our algorithm for solving the Google CAPTCHA. Being able to solve the Google CAPTCHA using a program would mean that there are some security issues which need to be considered at the earliest and this would assist us develop a better CAPTCHA.

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Section: Proposed Workmentioning

confidence: 99%

“…According to Kurt Alfred Kluver and Richard Zanibbi there are four properties which are desirable for a CAPTCHA, [1,2]namely:…”

Section: Introductionmentioning

confidence: 99%

Towards Solving the Google CAPTCHA

Mehta¹,

Sharma²

2014

IJCA

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“…However, the change of ρ does not significantly affect the advantage values compared to the change of k or the challenge selection methods. These values were derived from user success rates for existing image-based CAPTCHAs [11].…”

Section: Community-based Friend Selectionmentioning

confidence: 99%

Social Authentication: Harder Than It Looks

Kim

Tang

Anderson

2012

Financial Cryptography and Data Security

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Abstract. A number of web service firms have started to authenticate users via their social knowledge, such as whether they can identify friends from photos. We investigate attacks on such schemes. First, attackers often know a lot about their targets; most people seek to keep sensitive information private from others in their social circle. Against close enemies, social authentication is much less effective. We formally quantify the potential risk of these threats. Second, when photos are used, there is a growing vulnerability to face-recognition algorithms, which are improving all the time. Network analysis can identify hard challenge questions, or tell a social network operator which users could safely use social authentication; but it could make a big difference if photos weren't shared with friends of friends by default. This poses a dilemma for operators: will they tighten their privacy default settings, or will the improvement in security cost too much revenue?

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“…Interaction via Flex Now RIA, the next generation Web technology [6], has been applied widely, which combines interactive user experience with the deployment flexibility. The rich client technology in RIA can connect with existing back-end applications by asynchronous communication between client and server.…”

Section: B Implement Of Zhang's Captcha Based On Intelligentmentioning

confidence: 99%

Zhang's CAPTCHA architecture based on intelligent interaction via RIA

Zhang

2010

2010 2nd International Conference on Computer Engineering and Technology

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Abstract-To address the challenges in Web security based on CAPTCHA, we firstly analyze drawbacks, attack strategies and breaking methods of traditional CAPTCHAs, and propose a novel CAPTCHA architecture: Zhang's CAPTCHA based on intelligent interaction via RIA. It includes two lines of defenses against various types of attacks. The first line is constructed on rich client side via Flex through intelligent interaction such as actions of drag-drop similar to computer games. The second line is constructed on the server side by comparing random state parameters such as Session-ID and Hidden-data between rich client-side and server-side in order to prevent automated programs to circumvent CAPTCHA and directly attack the server. We use the proposed Zhang's CAPTCHA to develop two demos via Flex and JavaEE. The first demo requires user to drag specified one of five icons created randomly from the server and drop on a specified position according to a random question. The second demo requires user to select three of seven randomly numbered icons, drag them sequentially into a specified area. On the server side both of demos adopt the same comparison of random state parameters. The practice has shown that Zhang's CAPTCHA is too difficult for automated programs, but too easy for human, and is effective against a variety of attacks.

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Balancing usability and security in a video CAPTCHA

Cited by 87 publications

References 26 publications

Towards Solving the Google CAPTCHA

Towards Solving the Google CAPTCHA

Social Authentication: Harder Than It Looks

Zhang's CAPTCHA architecture based on intelligent interaction via RIA

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