明慧--Abstract

Abstract
The need to tell human and machines apart has surged due to abuse of automated 'bots'. However, several textual-image-based CAPTCHAs have been defeated recently, calling for the development of new anti-automation schemes. In this paper, we propose a simple yet effective visual CAPTCHA test by exchanging the content of non-overlapping regions in an image. We give in-depth analysis regarding the choice of parameter and image database during the test generation phase. We also contemplate possible ways, including 1) random guess, 2) collect and match, 3) image segmentation, to defeat the proposed test and provide counter-measures when necessary. Preliminary experimental results have validated the efficacy of the proposed CAPHCHA, although we expect that a large-scale experiment to collect and analyze user responses will contribute to optimal parameter settings.

由於全自動化機器人程式的濫用，人機辨識的需求已經暴增。然而，近年來一些以貼圖影像為基礎的CAPTCHA已經被反自動化組合的發展所取代。在這篇論文當中，我們提出一個簡單而有效的視覺CAPTCHA方法，它是在一張影像中，選出沒有影像重疊的部分做交換。我們在產生CAPTCHA的階段，根據參數的選擇及影像資料庫作深入的分析，同時也考量一些可能的方法去破解所提出的CAPTCHA，並且提供數據做為參考，而破解的方法包括1)隨機猜測，2)收集和比較，3)影像分割。初步實驗結果已經有效證實所提出的CAPTCHA，而我們期望有一個大規模的實驗來收集和分析使用者的使用結果，進而提供最佳的參數環境。