A CAPTCHA model based on visual psychophysics: Using the brain to distinguish between human users and automated computer bots

Demand for the use of online services such as free emails, social networks, and online polling is increasing at an exponential rate. Due to this, online service providers and retailers feel pressurised to satisfy the multitude of end-user expectations. Meanwhile, automated computer robots (known as “bots”) are targeting online retailers and service providers by acting as human users and providing false information in order to abuse their service provisioning. CAPTCHA is a set of challenge/response protocol, which was introduced to protect online retailers and service providers from misuse and automated computer attacks. Text-based CAPTCHAs are the most popular form, and are used by most online service providers to differentiate between the human users and bots. However, the vast majority of text-based CAPTCHAs have been broken using the Optical Character Recognition (OCR) techniques and thus, reinforces the need for developing a secure and robust CAPTCHA model. Security and usability are the two fundamental issues that pose a trade-off in the design of a CAPTCHA; a hard CAPTCHA model could also be difficult for human users to resolve, which affects its usability, and vice versa. The model developed in this study uses the unsurpassed abilities of the Human Visual System (HVS) to superimpose and integrate complex information presented in individual frames, using the mechanism of trans-saccadic memory. In this context, the model integrates in its design the concept of persistence of vision, which enables humans to see the world in a continuous fashion. Preliminary results from the proposed model based on this technique are encouraging. To ensure the usability of the proposed CAPTCHA model, we set the threshold for the ORO parameter at 40%. This ensured that our CAPTCHA strings would be recognised by human observers at a rate of over 99% (or as close to 100% as is realistic). In turn, when examining the robustness of our VICAP model to computer programme attacks, we can observe that for the traditional case of OCR recognition, based on a single-frame scenario, the Computer Recognition Success Rate (CRSR) was about 0%, while in the case of a multi-frame scenario, the CRSR could increase to up to 50%

CAPTCHaStar! A novel CAPTCHA based on interactive shape discovery

Over the last years, most websites on which users can register (e.g., email providers and social networks) adopted CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart) as a countermeasure against automated attacks. The battle of wits between designers and attackers of CAPTCHAs led to current ones being annoying and hard to solve for users, while still being vulnerable to automated attacks. In this paper, we propose CAPTCHaStar, a new image-based CAPTCHA that relies on user interaction. This novel CAPTCHA leverages the innate human ability to recognize shapes in a confused environment. We assess the effectiveness of our proposal for the two key aspects for CAPTCHAs, i.e., usability, and resiliency to automated attacks. In particular, we evaluated the usability, carrying out a thorough user study, and we tested the resiliency of our proposal against several types of automated attacks: traditional ones; designed ad-hoc for our proposal; and based on machine learning. Compared to the state of the art, our proposal is more user friendly (e.g., only some 35% of the users prefer current solutions, such as text-based CAPTCHAs) and more resilient to automated attacks.Comment: 15 page

Completely Automated Public Physical test to tell Computers and Humans Apart: A usability study on mobile devices

A very common approach adopted to fight the increasing sophistication and dangerousness of malware and hacking is to introduce more complex authentication mechanisms. This approach, however, introduces additional cognitive burdens for users and lowers the whole authentication mechanism acceptability to the point of making it unusable. On the contrary, what is really needed to fight the onslaught of automated attacks to users data and privacy is to first tell human and computers apart and then distinguish among humans to guarantee correct authentication. Such an approach is capable of completely thwarting any automated attempt to achieve unwarranted access while it allows keeping simple the mechanism dedicated to recognizing the legitimate user. This kind of approach is behind the concept of Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA), yet CAPTCHA leverages cognitive capabilities, thus the increasing sophistication of computers calls for more and more difficult cognitive tasks that make them either very long to solve or very prone to false negatives. We argue that this problem can be overcome by substituting the cognitive component of CAPTCHA with a different property that programs cannot mimic: the physical nature. In past work we have introduced the Completely Automated Public Physical test to tell Computer and Humans Apart (CAPPCHA) as a way to enhance the PIN authentication method for mobile devices and we have provided a proof of concept implementation. Similarly to CAPTCHA, this mechanism can also be used to prevent automated programs from abusing online services. However, to evaluate the real efficacy of the proposed scheme, an extended empirical assessment of CAPPCHA is required as well as a comparison of CAPPCHA performance with the existing state of the art. To this aim, in this paper we carry out an extensive experimental study on both the performance and the usability of CAPPCHA involving a high number of physical users, and we provide comparisons of CAPPCHA with existing flavors of CAPTCHA

GOTCHA Password Hackers!

We introduce GOTCHAs (Generating panOptic Turing Tests to Tell Computers and Humans Apart) as a way of preventing automated offline dictionary attacks against user selected passwords. A GOTCHA is a randomized puzzle generation protocol, which involves interaction between a computer and a human. Informally, a GOTCHA should satisfy two key properties: (1) The puzzles are easy for the human to solve. (2) The puzzles are hard for a computer to solve even if it has the random bits used by the computer to generate the final puzzle --- unlike a CAPTCHA. Our main theorem demonstrates that GOTCHAs can be used to mitigate the threat of offline dictionary attacks against passwords by ensuring that a password cracker must receive constant feedback from a human being while mounting an attack. Finally, we provide a candidate construction of GOTCHAs based on Inkblot images. Our construction relies on the usability assumption that users can recognize the phrases that they originally used to describe each Inkblot image --- a much weaker usability assumption than previous password systems based on Inkblots which required users to recall their phrase exactly. We conduct a user study to evaluate the usability of our GOTCHA construction. We also generate a GOTCHA challenge where we encourage artificial intelligence and security researchers to try to crack several passwords protected with our scheme.Comment: 2013 ACM Workshop on Artificial Intelligence and Security (AISec

CAPTCHA Accessibility Study of Online Forums

The rise of online forums has benefited disabled users, who take advantage of better communications and more inclusion into society. However, even with accessibility laws that are supposed to provide disabled people the same equal access as non-disabled users, sites have erected technical barriers, such as CAPTCHAs, that prevent users from taking full advantage of site capability. This study analyzes 150 online forums to determine if sites use CAPTCHAs, and what types are used. Each variety presents accessibility problems to disabled users and the results of the research show that most sites use text-based CAPTCHAs, but rarely provide alternatives that would help users with visual disabilities. The research presents alternatives that site designers may wish to consider in order to allow more disabled users to access their sites

The weak password problem: chaos, criticality, and encrypted p-CAPTCHAs

Vulnerabilities related to weak passwords are a pressing global economic and security issue. We report a novel, simple, and effective approach to address the weak password problem. Building upon chaotic dynamics, criticality at phase transitions, CAPTCHA recognition, and computational round-off errors we design an algorithm that strengthens security of passwords. The core idea of our method is to split a long and secure password into two components. The first component is memorized by the user. The second component is transformed into a CAPTCHA image and then protected using evolution of a two-dimensional dynamical system close to a phase transition, in such a way that standard brute-force attacks become ineffective. We expect our approach to have wide applications for authentication and encryption technologies.Comment: 5 pages, 6 figer