captcha and convolutional neural network
Post on 15-Jul-2015
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CAPTCHA
CAPTCHA •A CAPTCHA (an acronym for "Completely
Automated Public Turing test to tell Computers and Humans Apart")
Is a program that protects websites against bots by generating and grading tests that human can pass but current computers cannot .
Applications of CAPTCHAs
-Preventing comment spam in blogs
-Protecting websites registration
-Protecting email address from scrapers
-Online polls
-Preventing dictionary attacks
-Spam and worms
Types of CAPTCHAs
The most common is :
Visual CAPTCHA
Series of characters
and digits
Design of visual CAPTCHAs
For more difficulty and security we add:
-Text : color , font size , font type , style , set used
-Background : color , texture
-Translation , Rotation , Scaling ,over lapping , clutter , crossing lines , distortion , waving .
3D CAPTCHAs .
But Be careful
Design of visual CAPTCHAs
Breaking CAPTCHAs
1- Preprocessing .
2- Segmentation .
Breaking CAPTCHAs
3-Post segmentation (Normalizing) .
4- Recognition .
5- Post recognition .
Final Output is : “pvack”
Some CAPTCHA defeating projects
-Mori et all
-PWNTCHA from
-Microsoft research
-Vicarious (AI company)
Microsoft research results
Microsoft research results
Microsoft research results
Microsoft research results
So … where is the neural network
??
Convolutional Neural Network
Convolutional neural network
-Type of feed-forward MLP.
-Conv. Nets are inspired by biological processes in visual cortex.
-So it is used in image recognition and handwritten recognition .
-high performance in MNIST database .
-Designed by Yann Lecun .
Convolution
-Convolution is a common image processing technique that changes the intensities of a pixel to reflect the intensities of the surrounding pixels. A common use of convolution is to create image filters
Sparse Connectivity
Types of layers
-Convolutional layers .
-Kernel
-Feature Map or filter .
-Shared weights .
-Subsampling or pooling .
-Full connected layer (classification) .
Le Net
Modified Back propagation
-only a small change to the original algorithm. The gradient of a shared weight is simply the sum of the gradients of the parameters being shared.
w1=w2 ∆w1=∆w2
𝜕𝐸
𝜕𝑤2
𝜕𝐸
𝜕𝑤1
Sum
Solution !!!
-Image recognition Deep learning
-3D CAPTCHA.
-moving image .
-Audio CAPTCHA .
-MAPTCA (Mathematical CAPTCHA).
But…..
Conclusion
But …
It is trivial for AI.
“Any program that passes the tests generated by a CAPTCHA can be used to solve a hard unsolved AI problem”
Here we use knowledge for evil
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