Improve CAPTCHA's Security Using Gaussian Blur Filter

TL;DR

This paper proposes applying Gaussian Blur filters to visual CAPTCHAs to significantly reduce OCR readability while maintaining high human readability, enhancing web security against automated attacks.

Contribution

The novel application of Gaussian Blur to visual CAPTCHAs effectively impairs OCR recognition without affecting human users.

Findings

Gaussian Blur reduces OCR success rates significantly.

Human readability of CAPTCHAs remains high after applying Gaussian Blur.

Enhanced CAPTCHA security against automated attacks.

Abstract

Providing security for webservers against unwanted and automated registrations has become a big concern. To prevent these kinds of false registrations many websites use CAPTCHAs. Among all kinds of CAPTCHAs OCR-Based or visual CAPTCHAs are very common. Actually visual CAPTCHA is an image containing a sequence of characters. So far most of visual CAPTCHAs, in order to resist against OCR programs, use some common implementations such as wrapping the characters, random placement and rotations of characters, etc. In this paper we applied Gaussian Blur filter, which is an image transformation, to visual CAPTCHAs to reduce their readability by OCR programs. We concluded that this technique made CAPTCHAs almost unreadable for OCR programs but, their readability by human users still remained high.