Image CAPTCHA Research Articles

Robust CAPTCHA Image Generation Enhanced with Adversarial Example Methods

Robust CAPTCHA Image Generation Enhanced with Adversarial Example Methods

CAPTCHA Image Generation: Two-Step Style-Transfer Learning in Deep Neural Networks.

Mobile devices such as sensors are used to connect to the Internet and provide services to users. Web services are vulnerable to automated attacks, which can restrict mobile devices from accessing websites. To prevent such automated attacks, CAPTCHAs are widely used as a security solution. However, when a high level of distortion has been applied to a CAPTCHA to make it resistant to automated attacks, the CAPTCHA becomes difficult for a human to recognize. In this work, we propose a method for generating a CAPTCHA image that will resist recognition by machines while maintaining its recognizability to humans. The method utilizes the style transfer method, and creates a new image, called a style-plugged-CAPTCHA image, by incorporating the styles of other images while keeping the content of the original CAPTCHA. In our experiment, we used the TensorFlow machine learning library and six CAPTCHA datasets in use on actual websites. The experimental results show that the proposed scheme reduces the rate of recognition by the DeCAPTCHA system to 3.5% and 3.2% using one style image and two style images, respectively, while maintaining recognizability by humans.

Protection System against Phishing Attack

Phishing is indeed a personal or group attempt to acquire private data from unsuspecting victims, such as passwords, credit card information, etc. The first defense in a web implementation should be to strengthen the authentication system. A easy authentication based on username and password is not adequate for websites that provide critical economic transactions. In this document we suggested a fresh strategy to classifying phishing websites to fix the phishing issue. Phishing websites include a variety of signs provided in combination with the website within their content components as well as browser-based security indices. The use of images is researched to preserve the privacy of the captcha image by breaking down the original captcha image into two shares stored in separate database servers, so the original captcha image can only be revealed if both are available at the same time. Specific sheet images do not indicate the identity of the original captcha image. Once the user has been given the original captcha image, the password can be used. Several alternatives to tackle phishing have been suggested.

Digital Image Processing for Character Detection of Captcha Login Internet Banking Image using Matching Template

The development of the number of online shopping consumers in Indonesia is increasing. In 2016, research from e-Marketer estimated that it would reach 8.6 million people who shop through the internet. This figure increased from 7.9 million people in the previous year. The increasing number of people who know the internet along with the birth of generation Z (Gen Z) in the digital era makes changes in shopping habits that previously conventionally turned into online. Online transaction is an automatic ticket number that is used to differentiate transactions for each buyer. For example in the purchase transaction of goods in the online shop, each purchase transaction is distinguished through an additional three digits behind the nominal to facilitate payment into the seller’s account. The problem faced by the owner of the online shop is when BRI internet banking login to see account mutations, user authentication by entering the Captcha code. This process is repeated because there is a duration limitation for access to the system. It is necessary to check the account mutation automatically on a computer system that is able to read and recognize the character of the Captcha image. In this study, we propose the Template Matching method in recognizing characters in the captcha image. The dataset contains 300 images taken from the BRI internet banking website. The first step is to convert the extension from .png to .jpg. After the image is converted to extension .jpg the next step is pre-processing to correct the image of the noise that exists. Pre-processing result images that have been fixed are quality, then the separation of objects and background using Otsu. Then the process of labelling and segmentation. The characters are then processed using the Template Matching method so that they can be identified as numbers. The results of the experiments that have been carried out, found that the method we propose is able to recognize characters in the image with an accuracy rate of 90%. Errors in character recognition are due to characters that intersect, so when the results are processed the results do not match the ground truth.

Phishing Detection Using Visual Cryptography

Phishing is an attempt by an individual or a group to thieve personal confidential information such as passwords, credit card information etc from unsuspecting sufferer for burglary, financial gain and other criminal activities. The first defense should be strengthening the authentication mechanism in a web application. A simple username and password based authentication is not sufficient for web sites providing critical financial transactions. Here we have advised a new way for phishing websites classification to solve the problem of phishing. Phishing websites involves a collection of key within its content-parts as well as the browser-based security indicators provided along with the website. The use of images is try to keep the privacy of image captcha by dissolve the original image captcha into two shares that are stored in separate database servers such that the original image captcha can be acknowledged only when both are available together the individual sheet images do not confess the status of the original image captcha. Once the original image captcha is announced to the user it can be used as the password. Several solutions have been suggested to handle phishing.

CAPTCHA recognition based on deep convolutional neural network.

Aiming at the problems of low efficiency and poor accuracy of traditional CAPTCHA recognition methods, we have proposed a more efficient way based on deep convolutional neural network (CNN). The Dense Convolutional Network (DenseNet) has shown excellent classification performance which adopts cross-layer connection. Not only it effectively alleviates the vanishing-gradient problem, but also dramatically reduce the number of parameters. However, it also has caused great memory consumption. So we improve and construct a new DenseNet for CAPTCHA recognition (DFCR). Firstly, we reduce the number of convolutional blocks and build corresponding classifiers for different types of CAPTCHA images. Secondly, we input the CAPTCHA images of TFrecords format into the DFCR for model training. Finally, we test the Chinese or English CAPTCHAs experimentally with different numbers of characters. Experiments show that the new network not only keeps the primary performance advantages of the DenseNets but also effectively reduces the memory consumption. Furthermore, the recognition accuracy of CAPTCHA with the background noise and character adhesion is above 99.9%.

Development of a system for graphic captcha systems recognition using competing cellular automata

Peculiarities of the use of competing cellular automata for problems of recognition of complex captcha systems have been explored. For this purpose, the concept of competing cellular automata has been introduced and a mathematical model of their functioning and interaction has been developed. The mathematical model of competing cellular automata based on the set theory has been described to specify moving cellular automata, which shift to the neighboring states of characters and implement their transition rules in such a way. Based on this mathematical model, a recognition system for captcha images implemented in the code by means of JavaFX 2.0 technology has been developed, which allowed reaching the crossplatformness and correct functioning on different operating systems. The libraries of cellular automata have been developed for the English language. Each symbol of the alphabet is represented in the form of a state system, which is aligned with a cellular automaton with states describing the given symbol. We used Java programming language for development and OpenCV library for the ability to handle images which allowed us to achieve high-quality recognition results. The architecture of the developed system of recognition of complex captcha images in the form of diagrams of classes of the main blocks with detailed descriptions of each class has been considered. Computer experiments have been carried out with different sets of distorted characters used in actual captcha systems and recognition quality indices of the developed software obtained. It has been shown that the probability of obtaining the correct result of captcha image recognition exceeds 80 % with a degree of deformation of characters up to 20 %. With a degree of deformation of characters over 30 %, there is a high probability of false character recognition. The advantages of the method of text character recognition based on competing cellular automata include simplicity of rules of engagement, ability to parallelize the process of recognition easily, capability of recognition of distorted and partially overlapping characters that are the basis of modern captcha systems

An Approach for Chinese Character Captcha Recognition Using CNN

An approach using convolution neural network (CNN) to recognize Chinese Character Captcha captured from Tencent Security Center is proposed. 3500 commonly used Chinese characters are applied in the verification code system, so the problem is to detect, recognize and match the characters occurred in the two Captcha images. Firstly the characters in a Captcha image are analyzed and segmented, and each single character is a minimum unit in this paper. Secondly, a recognizing CNN is built and trained with a character library with 620,000 different character modes made by ourselves. Thirdly, the segmented characters from the Captcha image are input the network to finish recognition. The experiment result shows that the identification rate of the test data is as high as 99.4 percent after 25 iterations, and it is 1.75 percent higher when compared with another CNN model. It shows that the approach using CNN to do Chinese character Captcha recognition is feasible and it can provide a high level of accuracy.

Securing Online Transaction Using Visual Cryptography

Nowadays many people are using online financial transactions. This transaction needs to be secure. A rapid growth in E-Commerce market is seen in recent time throughout the world. With the ever-increasing use of online shopping, Debit or Credit card fraud and personal information security are major concerns for customers, merchants and banks specifically in the case of CNP (Card Not Present). This paper presents a new technique for providing limited data only that is required for fund transfer during online shopping thereby safeguarding customer data and to overcome these problems using visual cryptography. Visual Cryptography is a secret sharing scheme which owns the technique of sharing the visual information. The Captcha (image) is getting divided into two shares. The basic idea is that the secret captcha is divided into two irregular patterns of images called shares and they can be unraveled without any complicated cryptographic computation.

MULTI-FACTOR AUTHENTICATION USING A NOVEL APPROACH IN THE CLOUD

Cloud computing is a contemporary prototype to deliver services over the Internet. Cloud security is the most crucial issue in a cloud atmosphere either it is public cloud or community cloud. There is a vast scope to scrutinize data security enhancement in cloud storage. Authentication is anessential technology for information security, which is a mechanism to confirm proof of identities to obtain access of information in the system.Conventionally used authentication methods are rather securing data, but not smart enough and completely secured.In this paper, we have implemented a novel verification technique that associate with static username and password as a way in authentication followed by OTP based on the token generator method along with a digital signature and image captcha is an innovative factor to verify an each user. The solution aims at gaining confidentiality and integrity by making use of CP-ABHE (Ciphertext Policy-Attribute based Homomorphic Encryption algorithm) and user verification with Multi-Factor Authentication.Finally the efficiency of the system is examined with the help of the experimental results and discussions.

A novel method to authenticate in website using CAPTCHA‐based validation

AbstractWeb security has become vital, as the practice of internet is embryonic nowadays. To protect network from adversaries and to improve web security, researches has been done for a long time. The most solemn issue is phishing attack as well as access of web services by illicit users. Many users are not even sentient about phishing websites. Phishing is a kind of falsified approach employed by an attacker to get sensitive information from the users who are unaware of phishing attacks. User authorization is a noteworthy security measure that confirms the integrity of the user and ensures the confidentiality associated user data. The significant work done here is to prevent web users from entering into phishing websites and to provide web access only to authorized users via web server. Applications based on CAPTCHA provides more security against attacks. The proposed novel technique identifies phishing websites and authorized web access using Cropped Image CAPTCHA algorithm. The image CAPTCHA technique is not easily prone to web attacks moreover. Threshold values and conditions are defined. Based on this, Cropping‐Based Image CAPTCHA System appraises if the website is phishing website or legitimate website furthermore denies acquiescence to web admittance for unconstitutional users. Copyright © 2017 John Wiley & Sons, Ltd.

English

English

OTRCaptcha: A Novel Object and Text Recognition Based Image CAPTCHA

CAPTCHA is an important technology to prevent auto-script attack. Currently most of the CAPTCHA systems are text based, which firstly distort, rotate different characters and then use some obfuscation, aiming to make the text difficult to be recognized by auto- script while still can be learnt easily by real users. However, such kind of CAPTCHA schema either too simple, which can be attacked easily by using optimal character recognition (OCR) or machine learning based technology, or it is too complex that even real users cannot tell it. By observing such contradiction between security and usability, we propose a novel object and text recognition based image CAPTCHA system called OTRCaptcha. In OTRCaptcha, some object images (each has a label) and their names are attached into a background image respectively. In order to pass this CAPTCHA, users have to identify all the object images, labels within those objects and their names. Besides, users also need to identify the semantic relationship between object and its name. Both the theoretical analysis and experiment result show that OTRCapthcha can provide both high security and strong usability.

Securing Images in Cloud using Hyper Chaos with User Authentication

Security in the cloud is the top most concern. To achieve trust and preserve the privacy of data stored in third-party cloud storage has emerged as a key research area. To achieve this, several different techniques have been proposed based on cryptography. Secret sharing schemes and chaos based encryption have also been considered to address these issues of trust and privacy by various researchers. In this paper, we are proposing a new scheme to encrypt the private and sensitive images of users in the third party storage named as “Securing images in cloud using hyper chaos with user to solve the problem of authenticating users. Chaos based encryption with image captcha authentication using VCS is a major advantage of this scheme. Chaos based encryption is a very secure method for encryption. Many researchers have used the above technique but user authentication or authorization is not mentioned in their schemes. To increase more security we have included the authentication in the scheme. In this paper the authentication process is explored in depth and only the overview of encryption process is given. For securing the authentication logistic map is used to divide and shuffle the original image captcha into many blocks. The use of visual cryptography technique is explored to preserve the privacy of image captcha. Part of the image share will be kept with the image owner such that the original image captcha can be revealed only when both (user, owner) of the shares are simultaneously available. The individual share images do not reveal the identity of the original image captcha. Once the original image captcha is revealed after merging different shares, the user will be considered as authenticated user. Then only the encrypted key for the images will be transferred to the user. Dynamically generating the Captcha image by the system is one of the major advantage of the system.

MULTI-MODE DATA SECURITY FOR SECRET COMMUNICATION

Data Security in the current digitized era determines the ability of the system to protect, manage and distribute sensitive information. Privacy is the right of authorized users to ensure that confidential information maintained is being controlled and protected from unauthorized access or distribution. The major goals of data security are Confidentiality, Integrity, and Authentication. Text based passwords are the most common methods used for authentication. But these textual passwords are vulnerable to dictionary attacks, eves dropping and shoulder surfing. To address this problem, an approach for image based authentication has been proposed to authenticate a valid user with regards to enhancing the security of textual passwords which can be easily compromised. In this paper, algorithms for Image Cryptography, Image Steganography and Knowledge based Image CAPTCHA have been proposed to provide a one time communication. The image will be encrypted into two image shares at the server during password generation and the share returned to the client will be used as a token during authentication. At no time the entire password will be transmitted over the network or stored on any system during authentication. This hybrid multimode approach attempts to lessen the attacks towards password security thereby minimizing the risks of user impersonification and providing efficient means to transfer secret data using images. The proposed approach is well suited for private networks to transfer confidential messages without compromising the integrity of data. Keywords—authentication; visual cryptography; password; steganography; CAPTCHA -------------------------------------------------------------------***-------------------------------------------------------------------

Anti-Phishing Image Captcha Validation Scheme using Visual Cryptography

Evolution in the world of internet has given rise to several online attacks and the most common attack is phishing. Victims are tricked into providing such information by a combination of spoofing techniques and social engineering. Phishing is an attempt by an individual or a group to acquire sensitive information such as usernames, passwords, and credit card details from unsuspecting victims. In this paper we have proposed a new approach named as Antiphishing image captcha validation scheme using visual cryptography to solve the problem of phishing. Phishing websites are targeting the customers of banks and online payment services to steal sensitive data from victims. The use of images is explored to preserve the privacy of image captcha by decomposing the original image captcha into two shares that are stored in separate database servers such that the original image captcha can be revealed only when both are simultaneously available, the individual sheet images do not reveal the identity of the original image captcha. Once the original image captcha is revealed to the user it can be used as the password. Several solutions have been proposed to tackle phishing. Dynamically generating the captcha image by the system is one of the major advantages of the system. In this study, the authors shed light on the important features that distinguish phishing websites from legitimate ones and assess how good rule-based data mining classification techniques are in predicting phishing websites and which classification technique is proven to be more reliable.

A Technique for Web Security Using Mutual Authentication and Clicking-Cropping Based Image Captcha Technology

The major motto of my research is to develop a technique for web security using mutual authentication and clicking and cropping based image CAPTCHA technology. In our technique, we use two sections as registration and login. To create an account to use the application we use the registration section and to access the application we use the login section. We set five mandatory fields to login the application. The mandatory fields we give in login section should similar to the mandatory fields we gave while registration. The mandatory fields are checked with respect to the user id. The mandatory fields we set are user id, password, selecting image, number of clicks on image and cropping image. If the fields are same in the login section and registration section for a particular user id, the system will allow the user to access the application. Here, we incorporate three different features than the usual login section in the applications. The different features are selecting an image from a set of images and doing number clicks on that selected image and cropping a portion in that image. Our technique enhances the web security because of these added features.

The Recognition of CAPTCHA

CAPTCHA is a completely automated program designed to distinguish whether the user is a computer or human. As the problems of Internet security are worsening, it is of great significance to do research on CAPTCHA. This article starts from the recognition of CAPTCHAs, then analyses the weaknesses in its design and gives corresponding recognition proposals according to various weaknesses, finally offers suggestions related to the improvement of CAPTCHAs. Firstly, this article briefly introduces the basic steps during the decoding process and their principles. And during each step we choose methods which are better adapted to the features of different CAPTCHA images. Methods chosen are as followings: bimodal method in binarization, improved corrosion algorithm in denoising, projection segmentation method in denoised image processing and SVM in recognition. Then, we demonstrate detailed process through the samples taken from the online registration system of ICBC, show the recognition effect and correct the results according to the statistical data in the process. This article decodes CAPTCHAS from three other large banks in the same way but just provides the recognition results. Finally, this article offers targeted suggestions to the four banks based on the recognition effect and analysis process stated above.

FgCAPTCHA: Genetically Optimized Face Image CAPTCHA 5

The increasing use of smartphones, tablets, and other mobile devices poses a significant challenge in providing effective online security. CAPTCHAs, tests for distinguishing human and computer users, have traditionally been popular; however, they face particular difficulties in a modern mobile environment because most of them rely on keyboard input and have language dependencies. This paper proposes a novel image-based CAPTCHA that combines the touch-based input methods favored by mobile devices with genetically optimized face detection tests to provide a solution that is simple for humans to solve, ready for worldwide use, and provides a high level of security by being resilient to automated computer attacks. In extensive testing involving over 2600 users and 40000 CAPTCHA tests, fgCAPTCHA demonstrates a very high human success rate while ensuring a 0% attack rate using three well-known face detection algorithms.

Enhancing Web-Security with Stronger Captchas

. Captcha are used widely over the World Wide Web to prevent automated programs in order to scrape a data from websites. Captcha is a challenge response test used to ensure that the response is generated by a person not by a computer. Users are asked to read and type a string of distorted characters in order to ensure that the user is human or not. Automation is real problem for web application. Automated attacks can exploit many services: 1. Blogs 2. Forums 3. Phishing 4. Theft of data Registration Websites use CAPTCHA (completely automated public turing test to tell computers and human apart) systems to prevent the bot programs from wasting their resources. Today is the Era of where technologies are changes very rapidly. So spammers are hackers are also trying something new to cracking captcha. That’s why it is necessary to developing an advanced technology to generating a captcha. Just like simply generating a Captcha Images from text, or rotating an object within images.