{"title":"A Captcha Mechanism By Exchange Image Blocks","authors":"W. Liao","doi":"10.1109/ICPR.2006.40","DOIUrl":null,"url":null,"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, and 3) image segmentation, to defeat the proposed test and provide counter-measures when necessary. Preliminary experimental results have validated the efficacy of the proposed CAPTCHA, although we expect that a large-scale experiment to collect and analyze user responses contribute to optimal parameter settings","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th International Conference on Pattern Recognition (ICPR'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2006.40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
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, and 3) image segmentation, to defeat the proposed test and provide counter-measures when necessary. Preliminary experimental results have validated the efficacy of the proposed CAPTCHA, although we expect that a large-scale experiment to collect and analyze user responses contribute to optimal parameter settings