Random Handwritten CAPTCHA: Web Security with a Difference

Rao, M. Kameswara; Singh, Nipur

doi:10.5815/ijitcs.2012.09.07

Cited by 7 publications

(9 citation statements)

References 15 publications

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“…Rao, Mukta & Singh, and Nipur [19] identified that the bots have now become intelligent enough to crack through machineprinted CAPTCHAs. They covered the drawbacks of other CAPTCHA; Handwritten CAPTCHA images could be the solution.…”

Section: F Nlp Captchamentioning

confidence: 99%

Web Authentication Biometric 3D Animated CAPTCHA System Using Artificial Intelligence and Machine Learning Approach

Bora,

Dinesh Chandra Jain

2023

JAIT

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The internet and web security are integral aspects of our daily lives. Many commercial firms provide clients with internet services. For web access, it is assumed that only the genuine user, who is a human, will register. Yet automated hacking programs can also do registrations with fake data that consume a lot of bandwidth, slowing down or occasionally even shutting down websites, leading to Distributed denial-of-service (DDOS) attacks. Completely Automated Public Turing test to tell Computers and Human Apart (CAPTCHA) is the solution. Complex CAPTCHA is challenging for humans to recognize, but simple CAPTCHA is simple for AI to decipher. With the developments in neural networks and machine learning bots are mimicking humans and it is becoming difficult to distinguish humans and bots apart. This generated a need to think of some more innovative and novel CAPTCHA. Now, utilizing the same AIML approach to increase the efficacy of CAPTCHA and make it stronger against the bot attack. Biometric 3D Animated (B3DA) Algorithm proposed in this research is a novel approach based on the Face Detection AI algorithm along with handwritten 3D animated characters selected randomly to create a string which makes CAPTCHA simple that humans can identify but very difficult for bots. The test results have proven this to be a very robust CAPTCHA. The machine learning algorithm employed will keep on increasing the efficacy of this CAPTCHA each time the bot tries to break this.

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Section: F Nlp Captchamentioning

confidence: 99%

Web Authentication Biometric 3D Animated CAPTCHA System Using Artificial Intelligence and Machine Learning Approach

Bora,

Dinesh Chandra Jain

2023

JAIT

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“…In (6) an algorithm is proposed to distinguish between Persian and Arabic human user by using the features for each Arabic and Persian script, in this algorithm, random Arabic and Persian meaningless words are created and kept as image format, meanwhile, by applying some alterations, is presented to the user to ask him/her to categorise the displayed word. Another handwritten CAPTCHA images technique is presented by (7) to improve the security of web, this technique produces colored handwritten letters and words image, where randomness is associated within image to increase complexity of recognition. By exploiting the limits of Arabic OCRs in reading Arabic script in (8), Arabic CAPTCHA scheme is generated to be useful in Arabic countries, also to be beneficial in protective resource of the internet.…”

Section: Literature Reviewmentioning

confidence: 99%

Proposing a Scheme for Human Interactive Proof Test using Plasma Effect

al.¹

2019

Baghdad Sci.J

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Human Interactive Proofs (HIPs) are automatic inverse Turing tests, which are intended to differentiate between people and malicious computer programs. The mission of making good HIP system is a challenging issue, since the resultant HIP must be secure against attacks and in the same time it must be practical for humans. Text-based HIPs is one of the most popular HIPs types. It exploits the capability of humans to recite text images more than Optical Character Recognition (OCR), but the current text-based HIPs are not well-matched with rapid development of computer vision techniques, since they are either vey simply passed or very hard to resolve, thus this motivate that continuous efforts are required to improve the development of HIPs base text. In this paper, a new proposed scheme is designed for animated text-based HIP; this scheme exploits the gap between the usual perception of human and the ability of computer to mimic this perception and to achieve more secured and more human usable HIP. This scheme could prevent attacks since it's hard for the machine to distinguish characters with animation environment displayed by digital video, but it's certainly still easy and practical to be used by humans because humans are attuned to perceiving motion easily. The proposed scheme has been tested by many Optical Character Recognition applications, and it overtakes all these tests successfully and it achieves a high usability rate of 95%.

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“…In the same class of handwritten CAPTCHA, a random handwritten CAPTCHA was introduced by M. Rao and N. Singh in [13] where the CAPTCHA image consists of handwritten alphanumeric words. It is a randomized technique adopted in selecting the handwritten numbers and letters; also the appearance sequence of the CAPTCHA images with the color codes of text and digits are determined randomly at the run-time.…”

Section: Background and Related Workmentioning

confidence: 99%

“…Table2 shows different CAPTCHA systems and their adopted ranges. [13] 4 to 5 (without digits) [22] So, it was decided that the length of the proposed CAPTCHA should be between 5 to 8 characters, which is a reasonable length for a one-word text CAPTCHA.…”

Section: B Captcha's Lengthmentioning

confidence: 99%

Strong multilingual CAPTCHA based on handwritten characters

Aldosari

Al-Daraiseh

2016

2016 7th International Conference on Information and Communication Systems (ICICS)

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CAPTCHA (Completely Automated Public Turing Test to tell Computers and Humans Apart) is a kind of test which is commonly used by different websites on the Internet to differentiate between humans and automated bots. Most websites require the user to pass the CAPTCHA before signing up or filling out most forms. CAPTCHA today is even used on some mobile applications to provide a higher security level that can protect websites and mobile applications against malicious attacks by automated bots and spammers. In this paper, we present an advanced CAPTCHA technique; our technique essentially relies on employing the human recognition ability, which is not available in automated bots or machines, through leveraging the handwriting characteristics in designing CAPTCHA. Moreover, the proposed CAPTCHA technique adopts handwritten characters of four different languages (English, Arabic, Spanish, and French) to generate handwritten multilingual CAPTCHA text using characters from the four adopted languages. Furthermore, the initial experiments' results have shown a promising security level that the proposed CAPTCHA technique can provide.

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Random Handwritten CAPTCHA: Web Security with a Difference

Cited by 7 publications

References 15 publications

Web Authentication Biometric 3D Animated CAPTCHA System Using Artificial Intelligence and Machine Learning Approach

Web Authentication Biometric 3D Animated CAPTCHA System Using Artificial Intelligence and Machine Learning Approach

Proposing a Scheme for Human Interactive Proof Test using Plasma Effect

Strong multilingual CAPTCHA based on handwritten characters

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