CAPTCHA

Some researchers have proposed alternatives including image recognition CAPTCHAs which require users to identify simple objects in the images presented. The argument in favor of these schemes is that tasks like object recognition are more complex to perform than text recognition and therefore should be more resilient to machine learning based attacks.

Some researchers have proposed alternatives including image recognition CAPTCHAs which require users to identify simple objects in the images presented. The argument in favor of these schemes is that tasks like object recognition are more complex to perform than text recognition and therefore should be more resilient to machine learning based attacks.

Chew et al. published their work in the 7th International Information Security Conference, ISC'04, proposing three different versions of image recognition CAPTCHAs, and validating the proposal with user studies. It is suggested that one of the versions, the anomaly CAPTCHA, is best with 100% of human users being able to pass an anomaly CAPTCHA with at least 90% probability in 42 seconds.{{cite web |url=http://www.cs.berkeley.edu/~tygar/papers/Image_Recognition_CAPTCHAs/imagecaptcha.pdf |title=Image Recognition CAPTCHAs |publisher=Cs.berkeley.edu |access-date=2013-09-28 |archive-url=https://web.archive.org/web/20130510022240/http://www.cs.berkeley.edu/~tygar/papers/Image_Recognition_CAPTCHAs/imagecaptcha.pdf |archive-date=2013-05-10 |url-status=dead }} Datta et al. published their paper in the [[Association for Computing Machinery|ACM]] [[Multimedia]] '05 Conference, named IMAGINATION (IMAge Generation for INternet AuthenticaTION), proposing a systematic way to image recognition CAPTCHAs. Images are distorted so image recognition approaches cannot recognise them.{{cite web |url=http://infolab.stanford.edu/~wangz/project/imsearch/IMAGINATION/ACM05/ |title=Imagination Paper |publisher=Infolab.stanford.edu |access-date=2013-09-28 |archive-date=2 October 2013 |archive-url=https://web.archive.org/web/20131002170726/http://infolab.stanford.edu/~wangz/project/imsearch/IMAGINATION/ACM05/ |url-status=live }}

Chew et al. published their work in the 7th International Information Security Conference, ISC'04, proposing three different versions of image recognition CAPTCHAs, and validating the proposal with user studies. It is suggested that one of the versions, the anomaly CAPTCHA, is best with 100% of human users being able to pass an anomaly CAPTCHA with at least 90% probability in 42 seconds.{{cite web |url=http://www.cs.berkeley.edu/~tygar/papers/Image_Recognition_CAPTCHAs/imagecaptcha.pdf |title=Image Recognition CAPTCHAs |publisher=Cs.berkeley.edu |access-date=2013-09-28 |archive-url=https://web.archive.org/web/20130510022240/http://www.cs.berkeley.edu/~tygar/papers/Image_Recognition_CAPTCHAs/imagecaptcha.pdf |archive-date=2013-05-10 |url-status=dead }} Datta et al. published their paper in the [[Association for Computing Machinery|ACM]] [[Multimedia]] '05 Conference, named IMAGINATION (IMAge Generation for INternet AuthenticaTION), proposing a systematic way to image recognition CAPTCHAs. Images are distorted so image recognition approaches cannot recognize them.{{cite web |url=http://infolab.stanford.edu/~wangz/project/imsearch/IMAGINATION/ACM05/ |title=Imagination Paper |publisher=Infolab.stanford.edu |access-date=2013-09-28 |archive-date=2 October 2013 |archive-url=https://web.archive.org/web/20131002170726/http://infolab.stanford.edu/~wangz/project/imsearch/IMAGINATION/ACM05/ |url-status=live }}

Microsoft (Jeremy Elson, John R. Douceur, Jon Howell, and Jared Saul) claim to have developed Animal Species Image Recognition for Restricting Access (ASIRRA) which ask users to distinguish cats from dogs. Microsoft had a beta version of this for websites to use.{{cite web |url=https://www.microsoft.com/en-us/research/publication/asirra-a-captcha-that-exploits-interest-aligned-manual-image-categorization/ |archive-url=https://web.archive.org/web/20081215032402/http://research.microsoft.com/en-us/um/redmond/projects/asirra/ |archive-date=15 December 2008 |title=Asirra is a human interactive proof that asks users to identify photos of cats and dogs |website=[[Microsoft]] |url-status=dead }} They claim "Asirra is easy for users; it can be solved by humans 99.6% of the time in under 30 seconds. Anecdotally, users seemed to find the experience of using Asirra much more enjoyable than a text-based CAPTCHA." This solution was described in a 2007 paper to Proceedings of 14th ACM Conference on Computer and Communications Security (CCS).{{Cite conference |last1=Elson |first1=Jeremy |last2=Douceur |first2=John |last3=Howell |first3=Jon |last4=Saul |first4=Jared |date=October 2007 |title=Asirra: A CAPTCHA that Exploits Interest-Aligned Manual Image Categorization |url=https://www.microsoft.com/en-us/research/publication/asirra-a-captcha-that-exploits-interest-aligned-manual-image-categorization/ |conference=Proceedings of 14th ACM Conference on Computer and Communications Security |publisher=[[Microsoft]] |archive-url=https://web.archive.org/web/20081215032402/http://research.microsoft.com/en-us/um/redmond/projects/asirra/ |archive-date=15 December 2008 |access-date=15 September 2017 |url-status=live}} It was closed in October 2014.{{Cite web |title=After 8 years of operation, Asirra is shutting down effective October 1, 2014. Thank you to all of our users! |url=https://research.microsoft.com/en-us/projects/asirra/default.aspx |url-status=dead |archive-url=https://web.archive.org/web/20150207180225/https://research.microsoft.com/en-us/projects/asirra/default.aspx |archive-date=2015-02-07 |publisher=[[Microsoft]]}}

Microsoft (Jeremy Elson, John R. Douceur, Jon Howell, and Jared Saul) claim to have developed Animal Species Image Recognition for Restricting Access (ASIRRA) which ask users to distinguish cats from dogs. Microsoft had a beta version of this for websites to use.{{cite web |url=https://www.microsoft.com/en-us/research/publication/asirra-a-captcha-that-exploits-interest-aligned-manual-image-categorization/ |archive-url=https://web.archive.org/web/20081215032402/http://research.microsoft.com/en-us/um/redmond/projects/asirra/ |archive-date=15 December 2008 |title=Asirra is a human interactive proof that asks users to identify photos of cats and dogs |website=[[Microsoft]] |url-status=dead }} They claim "Asirra is easy for users; it can be solved by humans 99.6% of the time in under 30 seconds. Anecdotally, users seemed to find the experience of using Asirra much more enjoyable than a text-based CAPTCHA." This solution was described in a 2007 paper to Proceedings of 14th ACM Conference on Computer and Communications Security (CCS).{{Cite conference |last1=Elson |first1=Jeremy |last2=Douceur |first2=John |last3=Howell |first3=Jon |last4=Saul |first4=Jared |date=October 2007 |title=Asirra: A CAPTCHA that Exploits Interest-Aligned Manual Image Categorization |url=https://www.microsoft.com/en-us/research/publication/asirra-a-captcha-that-exploits-interest-aligned-manual-image-categorization/ |conference=Proceedings of 14th ACM Conference on Computer and Communications Security |publisher=[[Microsoft]] |archive-url=https://web.archive.org/web/20081215032402/http://research.microsoft.com/en-us/um/redmond/projects/asirra/ |archive-date=15 December 2008 |access-date=15 September 2017 |url-status=live}} It was closed in October 2014.{{Cite web |title=After 8 years of operation, Asirra is shutting down effective October 1, 2014. Thank you to all of our users! |url=https://research.microsoft.com/en-us/projects/asirra/default.aspx |url-status=dead |archive-url=https://web.archive.org/web/20150207180225/https://research.microsoft.com/en-us/projects/asirra/default.aspx |archive-date=2015-02-07 |publisher=[[Microsoft]]}}