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

Nouncaptcha: An Image-Based CAPTCHA Backed by an ESP Game Implementation

Honors (Bachelor's)Electrical Engineering and Computer ScienceElectrical Engineering and Computer ScienceNaval Architecture and Marine EngineeringUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/107736/1/cjjeakle.pd

Hunting CAPTCHA-solving bots

openToday, smart phones have become an integral part of modern human life. By increasing CPU power and energy efficiency of these types of equipment, almost all daily routines and even personal activities of people have become dependent on these devices. By knowing the importance of these equipment in today's human life and crucial role of them to protect personal sensitive information, security and authorized access to these data are indispensable requirement in any new methods in this field of study. Today, CAPTCHAs are used to protect smart phones and computers from robot access, however most of which are broken and hacked by robots and machine learning based method. Therefore, it is necessary to provide more accurate and comprehensive algorithm in order to identify robots and prevent them from entering mobile phones

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.

Using Novel Image-based Interactional Proofs and Source Randomization for Prevention of Web Bots

This work presents our efforts on preventing the web bots to illegitimately access web resources. As the first technique, we present SEMAGE (SEmantically MAtching imaGEs), a new image-based CAPTCHA that capitalizes on the human ability to define and comprehend image content and to establish semantic relationships between them. As the second technique, we present NOID - a "NOn-Intrusive Web Bot Defense system" that aims at creating a three tiered defence system against web automation programs or web bots. NOID is a server side technique and prevents the web bots from accessing web resources by inherently hiding the HTML elements of interest by randomization and obfuscation in the HTML responses. A SEMAGE challenge asks a user to select semantically related images from a given image set. SEMAGE has a two-factor design where in order to pass a challenge the user is required to figure out the content of each image and then understand and identify semantic relationship between a subset of them. Most of the current state-of-the-art image-based systems like Assira only require the user to solve the first level, i.e., image recognition. Utilizing the semantic correlation between images to create more secure and user-friendly challenges makes SEMAGE novel. SEMAGE does not suffer from limitations of traditional image-based approaches such as lacking customization and adaptability. SEMAGE unlike the current Text based systems is also very user friendly with a high fun factor. We conduct a first of its kind large-scale user study involving 174 users to gauge and compare accuracy and usability of SEMAGE with existing state-of-the-art CAPTCHA systems like reCAPTCHA (text-based) and Asirra (image-based). The user study further reinstates our points and shows that users achieve high accuracy using our system and consider our system to be fun and easy. We also design a novel server-side and non-intrusive web bot defense system, NOID, to prevent web bots from accessing web resources by inherently hiding and randomizing HTML elements. Specifically, to prevent web bots uniquely identifying HTML elements for later automation, NOID randomizes name/id parameter values of essential HTML elements such as "input textbox", "textarea" and "submit button" in each HTTP form page. In addition, to prevent powerful web bots from identifying special user-action HTML elements by analyzing the content of their accompanied "label text" HTML tags, we enhance NOID by adding a component, Label Concealer, which hides label indicators by replacing "label text" HTML tags with randomized images. To further prevent more powerful web bots identifying HTML elements by recognizing their relative positions or surrounding elements in the web pages, we enhance NOID by adding another component, Element Trapper, which obfuscates important HTML elements' surroundings by adding decoy elements without compromising usability. We evaluate NOID against five powerful state-of-the-art web bots including XRumer, SENuke, Magic Submitter, Comment Blaster, and UWCS on several popular open source web platforms including phpBB, Simple Machine Forums (SMF), and Wordpress. According to our evaluation, NOID can prevent all these web bots automatically sending spam on these web platforms with reasonable overhead