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It is increasingly becoming difficult for human beings to work on their dayto day life without going through the process of reverse Turing test, where theComputers tests the users to be humans or not. Almost every website and serviceproviders today have the process of checking whether their website is beingcrawled or not by automated bots which could extract valuable information fromtheir site. In the process the bots are getting more intelligent by the use ofDeep Learning techniques to decipher those tests and gain unwanted automatedaccess to data while create nuisance by posting spam. Humans spend aconsiderable amount of time almost every day when trying to decipher CAPTCHAs.The aim of this investigation is to check whether the use of a subset ofcommonly used CAPTCHAs, known as the text CAPTCHA is a reliable process forverifying their human customers. We mainly focused on the preprocessing stepfor every CAPTCHA which converts them in binary intensity and removes theconfusion as much as possible and developed various models to correctly labelas many CAPTCHAs as possible. We also suggested some ways to improve theprocess of verifying the humans which makes it easy for humans to solve theexisting CAPTCHAs and difficult for bots to do the same.

Deceiving computers in Reverse Turing Test through Deep Learning