Communication is faster than ever. Innovations in low cost network computing have brought an era in which people can effortlessly and instantaneously view and post opinions collaboratively with others across the world. With such an infrastructure of public message boards, chat rooms and instant messaging systems, there is also a large potential for abuse by people wishing to capitalize on such open services by posting unsolicited advertisements.
An entire industry has been constructed around the prevention of unsolicited electronic advertisements (SPAM). This thesis examines various techniques for preventing SPAM, focusing on Completely Automated Public Turing Tests to Tell Computers and Humans Apart (CAPTCHA), a challenge/response technique where an image is displayed with text that is heavily distorted. It also examines the feasibility of breaking CAPTCHA programmatically, alternatives to CAPTCHA based on filtering, improvements to CAPTCHA using photo recognition and avoiding the need for CAPTCHA using naïve approaches.
|Commitee:||Kizza, Joseph M., Thompson, Jack|
|School:||The University of Tennessee at Chattanooga|
|School Location:||United States -- Tennessee|
|Source:||MAI 49/04M, Masters Abstracts International|
|Keywords:||CAPTCHA, Filtering, OCR, Recognition|
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