We report a novel attack on two CAPTCHAs that have been widely deployed on the Internet, one being Google's home design and the other acquired by Google (i.e. reCAPTCHA). With a minor change, our attack program also works well on the latest ReCAPTCHA version, which uses a new defence mechanism that was unknown to us when we designed our attack. This suggests that our attack works in a fundamental level. Our attack appears to be applicable to a whole family of text CAPTCHAs that build on top of the popular segmentation-resistant mechanism of "crowding character together" for security. Next, we propose a novel framework that guides the application of our well-tested security engineering methodology for evaluating CAPTCHA robustness, and we propose a new general principle for CAPTCHA design.

@techreport{elahmad2011robustness, author = {El Ahmad, Ahmad S and Yan, Jeff and Tayara, Mohamad}, title = {The Robustness of Google CAPTCHAs}, year = {2011}, url = {http://homepages.cs.ncl.ac.uk/jeff.yan/google.pdf}, keywords = {captcha, character, google, image, ocr, recognition, segmentation}, abstract = {We report a novel attack on two CAPTCHAs that have been widely deployed on the Internet, one being Google's home design and the other acquired by Google (i.e. reCAPTCHA). With a minor change, our attack program also works well on the latest ReCAPTCHA version, which uses a new defence mechanism that was unknown to us when we designed our attack. This suggests that our attack works in a fundamental level. Our attack appears to be applicable to a whole family of text CAPTCHAs that build on top of the popular segmentation-resistant mechanism of "crowding character together" for security. Next, we propose a novel framework that guides the application of our well-tested security engineering methodology for evaluating CAPTCHA robustness, and we propose a new general principle for CAPTCHA design. } }

%0 = techreport %A = El Ahmad, Ahmad S and Yan, Jeff and Tayara, Mohamad %B = } %C = %D = 2011 %I = %T = The Robustness of Google CAPTCHAs} %U = http://homepages.cs.ncl.ac.uk/jeff.yan/google.pdf

@inproceedings{toepfer2011segmentation, author = {Toepfer, Martin and Kluegl, Peter and Hotho, Andreas and Puppe, Frank}, title = {Segmentation of References with Skip-Chain Conditional Random Fields for Consistent Label Transitions}, booktitle = {Workshop Notes of the LWA 2011 - Learning, Knowledge, Adaptation}, year = {2011}, url = {http://ki.informatik.uni-wuerzburg.de/papers/pkluegl/2011-LWA-SkYp.pdf}, keywords = {2011, chain, conditional, myown, references, segmentation} }

%0 = inproceedings %A = Toepfer, Martin and Kluegl, Peter and Hotho, Andreas and Puppe, Frank %B = Workshop Notes of the LWA 2011 - Learning, Knowledge, Adaptation %D = 2011 %T = Segmentation of References with Skip-Chain Conditional Random Fields for Consistent Label Transitions %U = http://ki.informatik.uni-wuerzburg.de/papers/pkluegl/2011-LWA-SkYp.pdf

@inproceedings{ScWaP09, author = {Scholz, S.W. and Wagner, R.}, title = {Classification in Marketing Science}, editor = {Okada, A. and Imaizumi, T. and Bock, H.-H. and Gaul, W.}, booktitle = {Cooperation in Classification and Data Analysis}, publisher = {Springer}, address = {Berlin}, year = {2009}, pages = {99 - 106}, keywords = {2009, Quantitative_Methoden_der_Marketingforschung, bi-secting, classification, k-means, myown, proceedings, segmentation, text_mining} }

%0 = inproceedings %A = Scholz, S.W. and Wagner, R. %B = Cooperation in Classification and Data Analysis %C = Berlin %D = 2009 %I = Springer %T = Classification in Marketing Science

@article{baerveldt1994influences, author = {Baerveldt, T. A. B.}, title = {Influences on and from the segmentation of networks: hypotheses and tests}, journal = { Social Networks}, year = {1994}, volume = {16}, pages = {213-232}, url = {http://www.prevention.psu.edu/events/documents/BaerveldtandSnijders1994_Influencesonandfromthesegmentation.pdf}, keywords = {social, segmentation, measures, networks, network, sna} }

%0 = article %A = Baerveldt, T. A. B. %D = 1994 %T = Influences on and from the segmentation of networks: hypotheses and tests %U = http://www.prevention.psu.edu/events/documents/BaerveldtandSnijders1994_Influencesonandfromthesegmentation.pdf