Breaking text-based CAPTCHAs with variable word and character orientation

Starostenko, Oleg; Cruz-Perez, Claudia; Uceda-Ponga, Fernando; Alarcón-Aquino, Vicente

doi:10.1016/j.patcog.2014.09.006

Cited by 60 publications

(28 citation statements)

References 7 publications

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“…The typical methods include vertical projection segmentation, horizontal projection segmentation, and guideline projection segmentation. Using (1), [61] defines three-color bar code to segment reCAPTCHA images:…”

Section: Segmentation Methods Based On Character Projectionmentioning

confidence: 99%

A Survey on Breaking Technique of Text-Based CAPTCHA

Chen

Luo²,

Guo

et al. 2017

Security and Communication Networks

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The CAPTCHA has become an important issue in multimedia security. Aimed at a commonly used text-based CAPTCHA, this paper outlines some typical methods and summarizes the technological progress in text-based CAPTCHA breaking. First, the paper presents a comprehensive review of recent developments in the text-based CAPTCHA breaking field. Second, a framework of text-based CAPTCHA breaking technique is proposed. And the framework mainly consists of preprocessing, segmentation, combination, recognition, postprocessing, and other modules. Third, the research progress of the technique involved in each module is introduced, and some typical methods of segmentation and recognition are compared and analyzed. Lastly, the paper discusses some problems worth further research.

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Section: Segmentation Methods Based On Character Projectionmentioning

confidence: 99%

A Survey on Breaking Technique of Text-Based CAPTCHA

Chen

Luo²,

Guo

et al. 2017

Security and Communication Networks

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“…These techniques are known as Scale Invariant Feature Transform (SIFT), Difference of Gaussian Points (DoG), Entropy Based Salient Region detector (EBSR), Harris and SUSAN corner detectors, Intensity Based and Edge Based Regions, Gradient based algorithms, and others. However, the computational complexity of these approaches frequently is too high in real-time applications and, in general, ideal distinctive properties of local features cannot be reached due to the simplicity of features themselves [9,21,22].…”

Section: Modern Techniques For Qr Code Detection and Recognitionmentioning

confidence: 99%

Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments

López-Rincón

Starostenko

Alarcón-Aquino

et al. 2017

Journal of Electrical and Computer Engineering

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Quick Response QR barcode detection in nonarbitrary environment is still a challenging task despite many existing applications for finding 2D symbols. The main disadvantage of recent applications for QR code detection is a low performance for rotated and distorted single or multiple symbols in images with variable illumination and presence of noise. In this paper, a particular solution for QR code detection in uncontrolled environments is presented. The proposal consists in recognizing geometrical features of QR code using a binary large object-(BLOB-) based algorithm with subsequent iterative filtering QR symbol position detection patterns that do not require complex processing and training of classifiers frequently used for these purposes. The high precision and speed are achieved by adaptive threshold binarization of integral images. In contrast to well-known scanners, which fail to detect QR code with medium to strong blurring, significant nonuniform illumination, considerable symbol deformations, and noising, the proposed technique provides high recognition rate of 80%-100% with a speed compatible to real-time applications. In particular, speed varies from 200 ms to 800 ms per single or multiple QR code detected simultaneously in images with resolution from 640 × 480 to 4080 × 2720, respectively.

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“…With regard to AI-based attacks, a wide range of success rates has been reported for different versions of reCAPTCHA: 4.9% [20], 11.6% [5], 24.7% [29], 31% [46], 40% [25,83], and even 55% [83].…”

Section: Security Of Farett-gender and Farett-genderandagementioning

confidence: 99%

“…This violation of authorization has been discussed widely in the security-related literature [1,98,14,85] and recent studies indicate that many state-of-the-art, text-based Captchas have been broken [7,12,18,25,37,56,65,83]. Consequently, the need for new (non text-based) types of Captchas is manifest, as suggested by several researchers [7,12,20,54,56].…”

Section: Introductionmentioning

confidence: 99%

Development of two novel face-recognition CAPTCHAs: A security and usability study

Schryen

Wagner

Schlegel

2016

Computers & Security

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CAPTCHAs are challenge-response tests that aim at preventing unwanted machines, including bots, from accessing web services while providing easy access for humans. Recent advances in artificial-intelligence based attacks show that the level of security provided by many state-ofthe-art text-based CAPTCHAs is declining. At the same time, techniques for distorting and obscuring the text, which are used to maintain the level of security, make text-based CAPTCHAs difficult to solve for humans, and thereby further degrade usability. The need for developing alternative types of CAPTCHAs which improve both, the current security and usability levels, has been emphasized by several researchers.With this study, we contribute to research through (1) the development of two new face recognition CAPTCHAs (Farett-Gender and FarettGender&Age), (2) the security analysis of both procedures, and (3) the provision of empirical evidence that one of the suggested CAPTCHAs (FarettGender) is similar to Google's reCAPTCHA and better than KCAPTCHA concerning effectiveness (error rates), superior to both regarding learnability and satisfaction but not efficiency.

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Breaking text-based CAPTCHAs with variable word and character orientation

Cited by 60 publications

References 7 publications

A Survey on Breaking Technique of Text-Based CAPTCHA

A Survey on Breaking Technique of Text-Based CAPTCHA

Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments

Development of two novel face-recognition CAPTCHAs: A security and usability study

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