CAPTCHA Design and Security Issues

Chow, Yang-Wai; Susilo, Willy; Thorncharoensri, Pairat

doi:10.1007/978-981-13-1483-4_4

Cited by 28 publications

(22 citation statements)

References 74 publications

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“…Our proposed method also is low-cost because (1) utilizing an open-source library itself is inexpensive for the hacking software development; (2) unlimited dataset can be generated through the revised software, which greatly decreases the training cost and efficiently increases the accuracy of modeling; and (3) the entire method and framework can be implemented in an economically affordable personal laptop.…”

Section: Discussionmentioning

confidence: 99%

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A Low-Cost Approach to Crack Python CAPTCHAs Using AI-Based Chosen-Plaintext Attack

Darling

2019

Applied Sciences

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CAPTCHA authentication has been challenged by recent technology advances in AI. However, many of the AI advances challenging CAPTCHA are either restricted by a limited amount of labeled CAPTCHA data or are constructed in an expensive or complicated way. In contrast, this paper illustrates a low-cost approach that takes advantage of the nature of open source libraries for an AI-based chosen-plaintext attack. The chosen-plaintext attack described here relies on a deep learning model created and trained on a simple personal computer in a low-cost way. It shows an efficient cracking rate over two open-source Python CAPTCHA Libraries, Claptcha and Captcha. This chosen-plaintext attack method has raised a potential security alert in the era of AI, particularly to small-business owners who use the open-source CAPTCHA libraries. The main contributions of this project include: (1) it is the first low-cost method based on chosen-plaintext attack by using the nature of open-source Python CAPTCHA libraries; (2) it is a novel way to combine TensorFlow object detection and our proposed peak segmentation algorithm with convolutional neural network to improve the recognition accuracy.

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Section: Discussionmentioning

confidence: 99%

“…CAPTCHA was designed to restrict malicious attacks to their sites. CAPTCHA has also been referred to as a reverse Turing Test [1] since the CAPTCHA system is designed to determine if a remote request is from a human [2].…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Approach to Crack Python CAPTCHAs Using AI-Based Chosen-Plaintext Attack

Darling

2019

Applied Sciences

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“…This type of captcha asks the user to identify some characters in an image deliberately rendered with some distortion and/or noise. Text-based captchas is widely used of since it is easily understood by most humans worldwide and since childhood we have been trained to recognize characters; it has a large brute force search space; its generation is easily automated without manual effort [2].…”

Section: Introductionmentioning

confidence: 99%

Applying Visual Cryptography to Enhance Text Captchas

et al. 2020

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Nowadays, lots of applications and websites utilize text-based captchas to partially protect the authentication mechanism. However, in recent years, different ways have been exploited to automatically recognize text-based captchas especially deep learning-based ways, such as, convolutional neural network (CNN). Thus, we have to enhance the text captchas design. In this paper, using the features of the randomness for each encoding process in visual cryptography (VC) and the visual recognizability with naked human eyes, VC is applied to design and enhance text-based captcha. Experimental results using two typical deep learning-based attack models indicate the effectiveness of the designed method. By using our designed VC-enhanced text-based captcha (VCETC), the recognition rate is in some degree decreased.

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“…Some of such suggestions were subsequently used to create CAPTCHAs for real-world systems, while other researchers developed alternative designs. The general principle behind CAPTCHAs is to use theoretically hard-AI problems as the basis of generate challenges that can only be solved by humans but not computers alone [3][4][5].…”

Section: Introductionmentioning

confidence: 99%