The robustness of animated text CAPTCHAs

PhD ThesisCAPTCHA is standard security technology that uses AI techniques to tells computer and human apart. The most widely used CAPTCHA are text-based CAPTCHA schemes. The robustness and usability of these CAPTCHAs relies mainly on the segmentation resistance mechanism that provides robustness against individual character recognition attacks. However, many CAPTCHAs have been shown to have critical flaws caused by many exploitable invariants in their design, leaving only a few CAPTCHA schemes resistant to attacks, including ReCAPTCHA and the Wikipedia CAPTCHA. Therefore, new alternative approaches to add motion to the CAPTCHA are used to add another dimension to the character cracking algorithms by animating the distorted characters and the background, which are also supported by tracking resistance mechanisms that prevent the attacks from identifying the main answer through frame-toframe attacks. These technologies are used in many of the new CAPTCHA schemes including the Yahoo CAPTCHA, CAPTCHANIM, KillBot CAPTCHAs, non-standard CAPTCHA and NuCAPTCHA. Our first question: can the animated techniques included in the new CAPTCHA schemes provide the required level of robustness against the attacks? Our examination has shown many of the CAPTCHA schemes that use the animated features can be broken through tracking attacks including the CAPTCHA schemes that uses complicated tracking resistance mechanisms. The second question: can the segmentation resistance mechanism used in the latest standard text-based CAPTCHA schemes still provide the additional required level of resistance against attacks that are not present missed in animated schemes? Our test against the latest version of ReCAPTCHA and the Wikipedia CAPTCHA exposed vulnerability problems against the novel attacks mechanisms that achieved a high success rate against them. The third question: how much space is available to design an animated text-based CAPTCHA scheme that could provide a good balance between security and usability? We designed a new animated text-based CAPTCHA using guidelines we designed based on the results of our attacks on standard and animated text-based CAPTCHAs, and we then tested its security and usability to answer this question. ii In this thesis, we put forward different approaches to examining the robustness of animated text-based CAPTCHA schemes and other standard text-based CAPTCHA schemes against segmentation and tracking attacks. Our attacks included several methodologies that required thinking skills in order to distinguish the animated text from the other animated noises, including the text distorted by highly tracking resistance mechanisms that displayed them partially as animated segments and which looked similar to noises in other CAPTCHA schemes. These attacks also include novel attack mechanisms and other mechanisms that uses a recognition engine supported by attacking methods that exploit the identified invariants to recognise the connected characters at once. Our attacks also provided a guideline for animated text-based CAPTCHAs that could provide resistance to tracking and segmentation attacks which we designed and tested in terms of security and usability, as mentioned before. Our research also contributes towards providing a toolbox for breaking CAPTCHAs in addition to a list of robustness and usability issues in the current CAPTCHA design that can be used to provide a better understanding of how to design a more resistant CAPTCHA scheme

Proposing a Scheme for Human Interactive Proof Test using Plasma Effect

            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%

On the security of text-based 3D CAPTCHAs

CAPTCHAs have become a standard security mechanism that are used to deter automated abuse of online services intended for humans. However, many existing CAPTCHA schemes to date have been successfully broken. As such, a number of CAPTCHA developers have explored alternative methods of designing CAPTCHAs. 3D CAPTCHAs is a design alternative that has been proposed to overcome the limitations of traditional CAPTCHAs. These CAPTCHAs are designed to capitalize on the human visual system\u27s natural ability to perceive 3D objects from an image. The underlying security assumption is that it is difficult for a computer program to identify the 3D content. This paper investigates the robustness of text-based 3D CAPTCHAs. In particular, we examine three existing text-based 3D CAPTCHA schemes that are currently deployed on a number of websites. While the direct use of Optical Character Recognition (OCR) software is unable to correctly solve these textbased 3D CAPTCHA challenges, we highlight certain patterns in the 3D CAPTCHAs can be exploited to identify important information within the CAPTCHA. By extracting this information, this paper demonstrates that automated attacks can be used to solve these 3D CAPTCHAs with a high degree of success

SECURITY AND USER EXPERIENCE: A HOLISTIC MODEL FOR CAPTCHA USABILITY ISSUES

CAPTCHA is a widely adopted security measure in the Web, and is designed to effectively distinguish humans and bots by exploiting human’s ability to recognize patterns that an automated bot is incapable of. To counter this, bots are being designed to recognize patterns in CAPTCHAs. As a result, CAPTCHAs are now being designed to maximize the difficulty for bots to pass human interaction proof tests, while making it quite an arduous task even for humans as well. The approachability of CAPTCHA is increasingly being questioned because of the inconvenience it causes to legitimate users. Irrespective of the popularity, CAPTCHA is indispensable if one wants to avoid potential security threats. We investigated the usability issues associated with CAPTCHA. We built a holistic model by identifying the important concepts associated with CAPTCHAs and its usability. This model can be used as a guide for the design and evaluation of CAPTCHAs

Human-artificial intelligence approaches for secure analysis in CAPTCHA codes

CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) has long been used to keep automated bots from misusing web services by leveraging human-artificial intelligence (HAI) interactions to distinguish whether the user is a human or a computer program. Various CAPTCHA schemes have been proposed over the years, principally to increase usability and security against emerging bots and hackers performing malicious operations. However, automated attacks have effectively cracked all common conventional schemes, and the majority of present CAPTCHA methods are also vulnerable to human-assisted relay attacks. Invisible reCAPTCHA and some approaches have not yet been cracked. However, with the introduction of fourth-generation bots accurately mimicking human behavior, a secure CAPTCHA would be hardly designed without additional special devices. Almost all cognitive-based CAPTCHAs with sensor support have not yet been compromised by automated attacks. However, they are still compromised to human-assisted relay attacks due to having a limited number of challenges and can be only solved using trusted devices. Obviously, cognitive-based CAPTCHA schemes have an advantage over other schemes in the race against security attacks. In this study, as a strong starting point for creating future secure and usable CAPTCHA schemes, we have offered an overview analysis of HAI between computer users and computers under the security aspects of open problems, difficulties, and opportunities of current CAPTCHA schemes.Web of Science20221art. no.

Bubble Captcha - A Start of the New Direction of Text Captcha Scheme Development

CAPTCHA, A Completely Automated Public Turing test to tell Computers and Humans Apart, iswell-known system widely used in all sorts of internet services around the world designated to secure the webfrom an automatic malicious activity. For almost two decades almost every system utilize a simple approach tothis problem containing a transcription of distorted letters from image to a text eld. The ground idea is to useimperfection of Optical Character Recognition algorithms against the computers. The development of OpticalCharacter recognition algorithms leads only to state, where the CAPTCHA schemes become more complex andhuman users have a great di culty with the transcription.This paper aims to present a new way of development of CAPTCHA schemes based more a human perception.The goal of this work is to implement new Captcha scheme and assess human capability to read unusual fontsnewer seen before

Research trends on CAPTCHA: A systematic literature

The advent of technology has crept into virtually all sectors and this has culminated in automated processes making use of the Internet in executing various tasks and actions. Web services have now become the trend when it comes to providing solutions to mundane tasks. However, this development comes with the bottleneck of authenticity and intent of users. Providers of these Web services, whether as a platform, as a software or as an Infrastructure use various human interaction proof’s (HIPs) to validate authenticity and intent of its users. Completely automated public turing test to tell computer and human apart (CAPTCHA), a form of IDS in web services is advantageous. Research into CAPTCHA can be grouped into two -CAPTCHA development and CAPTCH recognition. Selective learning and convolutionary neural networks (CNN) as well as deep convolutionary neural network (DCNN) have become emerging trends in both the development and recognition of CAPTCHAs. This paper reviews critically over fifty article publications that shows the current trends in the area of the CAPTCHA scheme, its development and recognition mechanisms and the way forward in helping to ensure a robust and yet secure CAPTCHA development in guiding future research endeavor in the subject domain

A case study of the robustness and the usability of CAPTCHA

The websites and network application experienced explosive growth in the past two decades. As the evolution of smartphones and mobile communication network have evolved, smart phone s user experience has been improved to a high level, and more and more people prefer to use smartphones. However, the development of techniques will not only increase the users experience but also bring threats of cracking. The development of techniques brought the potential threats to websites security. As a result, CAPTCHA, Completely Automated Public Turing test to tell Computers and Humans Apart, forms one of the methods to impede spamming attacks. As CAPTCHA s definition indicates, CAPTCHA should be recognized by humans easily while shouldn t be recognized computers. These two attributes of CAPTCHA can be considered as usability and robustness. Some CAPTCHA is difficult to be recognized by computers, but humans may also find difficult to recognize it. Therefore, the purpose of the thesis is to find out the balance between usability and robustness of CAPTCHA. Therefore, the related researches about the usability and the robustness of CAPTCHA will be reviewed, and the process of automatic CAPTCHA recognition will be Figured out and implemented by the author. The implementation will be based on the existed algorithms and a case study. The findings are the factors for improving CAPTCHA s robustness. They are from the each step of a specific process of automatic CAPTCHA recognition. Then the factors will be compared with the issues which are from the related usability research. The discussion will derive some possible ways, such as adding confusing characters and increasing data s diversity to improve robustness while keeping the usability according to the derived factors

Image Understanding for Automatic Human and Machine Separation.

PhDThe research presented in this thesis aims to extend the capabilities of human interaction proofs in order to improve security in web applications and services. The research focuses on developing a more robust and efficient Completely Automated Public Turing test to tell Computers and Human Apart (CAPTCHA) to increase the gap between human recognition and machine recognition. Two main novel approaches are presented, each one of them targeting a different area of human and machine recognition: a character recognition test, and an image recognition test. Along with the novel approaches, a categorisation for the available CAPTCHA methods is also introduced. The character recognition CAPTCHA is based on the creation of depth perception by using shadows to represent characters. The characters are created by the imaginary shadows produced by a light source, using as a basis the gestalt principle that human beings can perceive whole forms instead of just a collection of simple lines and curves. This approach was developed in two stages: firstly, two dimensional characters, and secondly three-dimensional character models. The image recognition CAPTCHA is based on the creation of cartoons out of faces. The faces used belong to people in the entertainment business, politicians, and sportsmen. The principal basis of this approach is that face perception is a cognitive process that humans perform easily and with a high rate of success. The process involves the use of face morphing techniques to distort the faces into cartoons, allowing the resulting image to be more robust against machine recognition. Exhaustive tests on both approaches using OCR software, SIFT image recognition, and face recognition software show an improvement in human recognition rate, whilst preventing robots break through the tests