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.
Interactive CAPTCHAs mitigate the relay attack threat. For example, Noise CAPTCHA @cite_23 presents a transparent noisy image overlapped to a noisy background. The user needs to drag this image until he can recognize a well formed text. Cursor CAPTCHA @cite_19 changes the appearance of mouse cursor into another random object. The user needs to overlap the cursor on the identical object placed in a random generated image. Jigsaw CAPTCHA @cite_15 reprises the classical jigsaw puzzle. Indeed, the user needs to correctly rearrange the pieces of a jigsaw. Finally, PlayThru @cite_3 asks the user to solve a randomly generated mini-game. These mini-games require to drag objects on their correct spots.
@cite_19 @cite_15 @cite_3 @cite_23
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Some Internet Web sites for providing services to their customers, ask them to register in the Web site. Unfortunately hackers write programs to make automatic false enrollments which waste the Web site's resources. To solve this problem, systems known as CAPTCHA (completely automated public Turing test to tell computers and humans apart) have been introduced to distinguish between human user and computer program. One of the CAPTCHA methods is collage CAPTCHA. In this method some shapes are shown with distortion and the user is asked to choose a specific object. In this paper we increase the resistance of this method to attacks. For this purpose, we also show some other objects on the right of the screen. Some of these objects are same as the previous objects, but have the different shapes. Now we ask the user to choose a specific object and also its same object on the right of the screen. The user will be passed the test if he chooses the two similar objects correctly. In this method because the computer program should also recognize the similar object, the possibility of passing the test by computer is more reduced. Most commonly used CAPTCHAs are text-based CAPTCHAs which relay on the distortion of texts in the background image. With the development of automated computer vision techniques, which have been designed to remove noise and segment the distorted strings to make characters readable for OCR, traditional text-based CAPTHCAs are not considered safe anymore for authentication. A novel image based CAPTCHA which involves in solving a jigsaw puzzle is presented in this paper. An image is divided into an niAn (n=3, 4 or 5, depends on security level) pieces to construct the jigsaw puzzle CAPTCHA. Only two of the pieces are misplaced from their original positions. Users are required to find the two pieces and swap them. Considering the previous works which are devoted to solving jigsaw puzzles using edge matching technique, the edges of all pieces are processed with glitch treatment to prevent the computer automatic solving. Experiments and security analysis proved that human users can complete the CAPTCHA verification quickly and accurately, but computers rarely can. It is a promising substitution to the current text-based CAPTCHA. In this paper, a CAPTCHA is presented based on the masking characteristics of the Human Visual System (HVS). Knowing that noise can be masked by high activity regions and showing that edges can be masked by noise for a human observer while still being detected by machines, the suggested CAPTCHA is composed of English alphabets that are picked randomly and written with a combination of texture and edges with added noise such as to deceive the machine by randomly changing the visibility of characters for humans. The proposed CAPTCHA is highly legible and robust to brute-force attacks and sophisticated Object Character Recognition (OCR) segmentation algorithms. CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) is a simple test that is easy for humans but extremely difficult for computers to solve. CAPTCHA has been widely used in commercial websites such as web-based email providers, TicketMaster, GoDaddy, and Facebook to protect their resources from attacks initiated by automatic scripts. By design, CAPTCHA is unable to distinguish between a human attacker and a legitimate human user. This leaves websites using CAPTCHA vulnerable to 3rd party human CAPTCHA attacks. In order to demonstrate the vulnerabilities in existing CAPTCHA technologies we develop a new streamlined human-based CAPTCHA attack that uses Instant Messenger infrastructure. Facing this serious human-based attack threat, we then present a new defense system called Interactive CAPTCHA (iCAPTCHA), which is the next generation of CAPTCHA technology providing the first steps toward defending against 3rd party human CAPTCHA attacks. iCAPTCHA requires a user to solve a CAPTCHA test via a series of user interactions. The multi-step back-and-forth traffic between client and server amplifies the statistical timing difference between a legitimate user and a human solver, which enables better attack detection performance. A performance and usability study of iCAPTCHA shows the proposed scheme is effective in attack detection, is easy to use, and is a viable replacement of the current text-based CAPTCHA.