Visual cryptography for gray-level images by dithering techniques
Pattern Recognition Letters
Telling humans and computers apart automatically
Communications of the ACM - Information cities
A survey of image spamming and filtering techniques
Artificial Intelligence Review
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Abuse of free Internet resources and services from false account creation, to spam, to identity theft, excessive bandwidth usage, or even vote stuffing online polls is a big problem. The Completely Automatic Public Turing Test to tell Computers and Humans Apart (CAPTCHA) controls access to resources but automated systems are increasingly adept at overcoming them. In this paper a method of access control is introduced as an extra layer of security on top of existing CAPTCHA implementations. It uses visual encryption to encrypt images, which are presented to clients like a CAPTCHA. It's purpose is to compress many sub-images into a small image format that humans can decode visually but is hard for automated systems due to decrypting overhead, and having to process more images to find the hidden image. This paper introduces visual encryption as a viable method to encrypt CAPTCHAs, and tests a prototype to measure how efficiently users can find them. It also measures whether this method could impede a real CAPTCHA breaker. Results show humans detect images within 16--33 seconds, and deciphering images is almost 100%. Estimates on CAPTCHA breaking benchmarks show automated systems would be slowed significantly, even assuming the image is found and decoded. As sub-images increase, humans can process the visually encrypted images faster than automated systems can.