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Proceedings ArticleDOI

Text-based CAPTCHA strengths and weaknesses

TLDR
It is found that 13 current visual CAPTCHAs based on distorted characters that are augmented with anti-segmentation techniques from popular web sites are vulnerable to automated attacks.
Abstract
We carry out a systematic study of existing visual CAPTCHAs based on distorted characters that are augmented with anti-segmentation techniques. Applying a systematic evaluation methodology to 15 current CAPTCHA schemes from popular web sites, we find that 13 are vulnerable to automated attacks. Based on this evaluation, we identify a series of recommendations for CAPTCHA designers and attackers, and possible future directions for producing more reliable human/computer distinguishers.

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Citations
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Journal ArticleDOI

Machine learning

TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Journal ArticleDOI

A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs

TL;DR: This work introduces recursive cortical network (RCN), a probabilistic generative model for vision in which message-passing–based inference handles recognition, segmentation, and reasoning in a unified manner and outperforms deep neural networks on a variety of benchmarks while being orders of magnitude more data-efficient.
Book ChapterDOI

HelDroid: Dissecting and Detecting Mobile Ransomware

TL;DR: HelDroid is presented, a fast, efficient and fully automated approach that recognizes known and unknown scareware and ransomware samples from goodware, based on detecting the "building blocks" that are typically needed to implement a mobile ransomware application.

The end is nigh: generic solving of text-based CAPTCHAs

TL;DR: The effectiveness and universality of the results suggests that combining segmentation and recognition is the next evolution of catpcha solving, and that it supersedes the sequential approach used in earlier works.
Proceedings ArticleDOI

Yet Another Text Captcha Solver: A Generative Adversarial Network Based Approach

TL;DR: This paper presents a generic, yet effective text captcha solver based on the generative adversarial network and demonstrates that the attack is generally applicable and can bypass the advanced security features employed by most modern text captcha schemes.
References
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Journal ArticleDOI

Gradient-based learning applied to document recognition

TL;DR: In this article, a graph transformer network (GTN) is proposed for handwritten character recognition, which can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters.
Journal ArticleDOI

Support-Vector Networks

TL;DR: High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.
Journal ArticleDOI

A Computational Approach to Edge Detection

TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Journal ArticleDOI

Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images

TL;DR: The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
Proceedings ArticleDOI

Object recognition from local scale-invariant features

TL;DR: Experimental results show that robust object recognition can be achieved in cluttered partially occluded images with a computation time of under 2 seconds.