Automated image based CAPTCHA solver

CAPTCHA is known as “Completely Automated Public Turing Test to tell Computers and Humans Apart”. Text-based CAPTCHA is the most common technique used across the internet to detect bot from attacking an online system. An image of distorted word is generated as computer program will have difficulty t...

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Bibliographic Details
Main Author:	Choong, Kai Bin
Format:	Thesis
Language:	English
Published:	2018
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/78552/1/ChoongKaiBinMFKE2018.pdf
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id	my-utm-ep.78552
record_format	uketd_dc
spelling	my-utm-ep.785522018-08-27T03:22:27Z Automated image based CAPTCHA solver 2018-01 Choong, Kai Bin TK Electrical engineering. Electronics Nuclear engineering CAPTCHA is known as “Completely Automated Public Turing Test to tell Computers and Humans Apart”. Text-based CAPTCHA is the most common technique used across the internet to detect bot from attacking an online system. An image of distorted word is generated as computer program will have difficulty to read it. In fact, human can read the text in the image CAPTCHA easily. This will help to prevent websites from being attacked by automated scripts. Hence, CAPTCHA should be considered as a win-win strategy that is able to provide security for websites from bot attack but do not cause any disturbance to the user. On the other hand, due to the advancement of pattern recognition technology, current text based CAPTCHA may not be robust enough to defend the intelligence of bot. Thus, in this project, a CAPTCHA solving algorithm is developed to investigate on the strength of CAPTCHA in defeating the bot. Besides, it is also aimed to find out the gap of text based CAPTCHA which in turn helps to develop a more robust CAPTCHA. The project methodology can be broken down into pre-processing, segmentation and character recognition. In preprocessing stage, CAPTCHA image is converted to grey image. After that, lines and dots are removed in order to get back the original word in the image. Segmentation is carried out to crop out individual characters that exist in the image CAPTCHA for character recognition purpose. After the characters have been extracted, the characters are recognized by matching them with the database. If all the characters can be recognized, the text based CAPTCHA is broken. The CAPTCHA solving algorithm was developed with MATLAB, so that it can be trained against a custom dataset. It is able to break ASP.NET text-based CAPTCHA with accuracy of 96 % and 98.86 % in term of word and character recognition respectively. 2018-01 Thesis http://eprints.utm.my/id/eprint/78552/ http://eprints.utm.my/id/eprint/78552/1/ChoongKaiBinMFKE2018.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:108397 masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Choong, Kai Bin Automated image based CAPTCHA solver
description	CAPTCHA is known as “Completely Automated Public Turing Test to tell Computers and Humans Apart”. Text-based CAPTCHA is the most common technique used across the internet to detect bot from attacking an online system. An image of distorted word is generated as computer program will have difficulty to read it. In fact, human can read the text in the image CAPTCHA easily. This will help to prevent websites from being attacked by automated scripts. Hence, CAPTCHA should be considered as a win-win strategy that is able to provide security for websites from bot attack but do not cause any disturbance to the user. On the other hand, due to the advancement of pattern recognition technology, current text based CAPTCHA may not be robust enough to defend the intelligence of bot. Thus, in this project, a CAPTCHA solving algorithm is developed to investigate on the strength of CAPTCHA in defeating the bot. Besides, it is also aimed to find out the gap of text based CAPTCHA which in turn helps to develop a more robust CAPTCHA. The project methodology can be broken down into pre-processing, segmentation and character recognition. In preprocessing stage, CAPTCHA image is converted to grey image. After that, lines and dots are removed in order to get back the original word in the image. Segmentation is carried out to crop out individual characters that exist in the image CAPTCHA for character recognition purpose. After the characters have been extracted, the characters are recognized by matching them with the database. If all the characters can be recognized, the text based CAPTCHA is broken. The CAPTCHA solving algorithm was developed with MATLAB, so that it can be trained against a custom dataset. It is able to break ASP.NET text-based CAPTCHA with accuracy of 96 % and 98.86 % in term of word and character recognition respectively.
format	Thesis
qualification_level	Master's degree
author	Choong, Kai Bin
author_facet	Choong, Kai Bin
author_sort	Choong, Kai Bin
title	Automated image based CAPTCHA solver
title_short	Automated image based CAPTCHA solver
title_full	Automated image based CAPTCHA solver
title_fullStr	Automated image based CAPTCHA solver
title_full_unstemmed	Automated image based CAPTCHA solver
title_sort	automated image based captcha solver
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2018
url	http://eprints.utm.my/id/eprint/78552/1/ChoongKaiBinMFKE2018.pdf
_version_	1747818013264969728

Automated image based CAPTCHA solver

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