{"id":"https://openalex.org/W1667580224","doi":null,"title":"The end is nigh: generic solving of text-based CAPTCHAs","display_name":"The end is nigh: generic solving of text-based CAPTCHAs","publication_year":2014,"publication_date":"2014-08-19","ids":{"openalex":"https://openalex.org/W1667580224","mag":"1667580224"},"language":"en","primary_location":{"id":"mag:1667580224","doi":null,"is_oa":false,"landing_page_url":"https://cdn.elie.net/publications/the-end-is-nigh-generic-solving-of-text-based-captchas.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058819105","display_name":"Elie Bursztein","orcid":"https://orcid.org/0000-0003-0316-6906","observed_orcids":["https://orcid.org/0000-0003-0316-6906"]},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elie Bursztein","raw_affiliation_strings":["Google\u2020#TAB#"],"raw_orcid":"https://orcid.org/0000-0003-0316-6906","affiliations":[{"raw_affiliation_string":"Google\u2020#TAB#","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013476470","display_name":"Jonathan Aigrain","orcid":"https://orcid.org/0000-0001-6449-6525","observed_orcids":["https://orcid.org/0000-0001-6449-6525"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan Aigrain","raw_affiliation_strings":["Stanford University"],"raw_orcid":"https://orcid.org/0000-0001-6449-6525","affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059568038","display_name":"Angelika Moscicki","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Angelika Moscicki","raw_affiliation_strings":["Google\u2020#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google\u2020#TAB#","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101897622","display_name":"John C. Mitchell","orcid":"https://orcid.org/0000-0002-0024-860X","observed_orcids":["https://orcid.org/0000-0002-0024-860X"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John C. Mitchell","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":18.4464,"has_fulltext":false,"cited_by_count":131,"citation_normalized_percentile":{"value":0.99083168,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3","last_page":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11800","display_name":"User Authentication and Security Systems","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11800","display_name":"User Authentication and Security Systems","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.002199999988079071,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.0020000000949949026,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/captcha-solving","display_name":"CAPTCHA solving","score":0.9190000295639038},{"id":"https://openalex.org/keywords/character-segmentation","display_name":"character segmentation","score":0.6029999852180481},{"id":"https://openalex.org/keywords/character-recognition","display_name":"character recognition","score":0.9240000247955322},{"id":"https://openalex.org/keywords/recaptcha","display_name":"reCAPTCHA","score":0.5929999947547913},{"id":"https://openalex.org/keywords/captcha-security","display_name":"CAPTCHA security","score":0.6809999942779541}],"concepts":[{"id":"https://openalex.org/C163339463","wikidata":"https://www.wikidata.org/wiki/Q484598","display_name":"CAPTCHA","level":2,"score":0.9844322204589844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7664306163787842},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6588190793991089},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6545860171318054},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6220385432243347},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.6008431315422058},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.5921238660812378},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.519279956817627},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5027098655700684},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49332395195961},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.48794835805892944},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.44320714473724365},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.4349164068698883},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3513510525226593},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.10196149349212646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10003948211669922},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:1667580224","doi":null,"is_oa":false,"landing_page_url":"https://cdn.elie.net/publications/the-end-is-nigh-generic-solving-of-text-based-captchas.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W87564900","https://openalex.org/W112869242","https://openalex.org/W182783924","https://openalex.org/W628837208","https://openalex.org/W1488616864","https://openalex.org/W1532325895","https://openalex.org/W1560502112","https://openalex.org/W1610836425","https://openalex.org/W1827297289","https://openalex.org/W1969670714","https://openalex.org/W1971657180","https://openalex.org/W1995444699","https://openalex.org/W2003735219","https://openalex.org/W2006500012","https://openalex.org/W2088301450","https://openalex.org/W2099256741","https://openalex.org/W2100921332","https://openalex.org/W2105523261","https://openalex.org/W2108724351","https://openalex.org/W2112796928","https://openalex.org/W2113321599","https://openalex.org/W2116241551","https://openalex.org/W2120480077","https://openalex.org/W2120801852","https://openalex.org/W2123761123","https://openalex.org/W2136922672","https://openalex.org/W2147019420","https://openalex.org/W2151401338","https://openalex.org/W2153601419","https://openalex.org/W2156749117","https://openalex.org/W2168727550","https://openalex.org/W2171973097","https://openalex.org/W2188737212","https://openalex.org/W2196513764","https://openalex.org/W2253807446","https://openalex.org/W2294312922","https://openalex.org/W2470688280","https://openalex.org/W2950789693","https://openalex.org/W4239510810"],"related_works":["https://openalex.org/W7100118045","https://openalex.org/W2130563349","https://openalex.org/W7098689576","https://openalex.org/W6902020950","https://openalex.org/W4385679715","https://openalex.org/W3180968616","https://openalex.org/W1488616864","https://openalex.org/W7006830346","https://openalex.org/W2284177433","https://openalex.org/W3012731629"],"abstract_inverted_index":{"Over":[0],"the":[1,18,22,44,77,85,95,126,129,155,160,175,186,197,212,220,268,278,299],"last":[2],"decade,":[3],"it":[4,158,276],"has":[5,34,65],"become":[6],"well-established":[7],"that":[8,48,58,120,145,227,240,262,275],"a":[9,36,40,54,110,117],"captcha's":[10],"ability":[11],"to":[12,30,83,113,124,140,170,183,195,211,238,245,293],"withstand":[13],"automated":[14],"solving":[15,31,114],"lies":[16],"in":[17,116,200,249,282,298],"difficulty":[19],"of":[20,258,271],"segmenting":[21],"image":[23,45],"into":[24,46],"individual":[25,50],"characters.":[26],"The":[27,254],"standard":[28],"approach":[29,64,112,168,177,242,280,288],"captchas":[32,115,297],"automatically":[33],"been":[35,66],"sequential":[37,279],"process":[38],"wherein":[39],"segmentation":[41,78,127,264],"algorithm":[42,91,139,213],"splits":[43],"segments":[47],"contain":[49],"characters,":[51],"followed":[52],"by":[53,76,101],"character":[55,96,234],"recognition":[56,130,266],"step":[57,119],"uses":[59,121],"machine":[60,122],"learning.":[61],"While":[62],"this":[63],"effective":[67],"against":[68,219],"particular":[69],"captcha":[70,106,172,189],"schemes,":[71],"its":[72,215],"generality":[73],"is":[74,81,92,146,243,267],"limited":[75],"step,":[79],"which":[80],"hand-crafted":[82,164],"defeat":[84,246],"distortion":[86],"at":[87],"hand.":[88],"No":[89],"general":[90,252],"known":[93],"for":[94,162],"collapsing":[97,235],"anti-segmentation":[98],"technique":[99],"used":[100,281],"most":[102],"prominent":[103],"real":[104,187],"world":[105,188],"schemes.\r\n\r\nThis":[107],"paper":[108],"introduces":[109],"novel":[111],"single":[118],"learning":[123],"attack":[125],"and":[128,143,205,223,256,265,274],"problems":[131],"simultaneously.":[132],"Performing":[133],"both":[134],"operations":[135],"jointly":[136],"allows":[137],"our":[138,167,241,259,287],"exploit":[141],"information":[142],"context":[144],"not":[147],"available":[148],"when":[149],"they":[150],"are":[151],"done":[152],"sequentially.":[153],"At":[154],"same":[156],"time,":[157],"removes":[159],"need":[161],"any":[163,209],"component,":[165],"making":[166],"generalize":[169],"new":[171],"schemes":[173,190,226],"where":[174],"previous":[176],"can":[178],"not.":[179],"We":[180],"were":[181],"able":[182,244],"solve":[184],"all":[185],"we":[191],"evaluated":[192],"accurately":[193],"enough":[194],"consider":[196],"scheme":[198],"insecure":[199],"practice,":[201],"including":[202],"Yahoo":[203],"(5.33%)":[204],"ReCaptcha":[206],"(33.34%),":[207],"without":[208],"adjustments":[210],"or":[214],"parameters.":[216],"Our":[217],"success":[218],"Baidu":[221],"(38.68%)":[222],"CNN":[224],"(51.09%)":[225],"use":[228],"occluding":[229,247],"lines":[230,248],"as":[231,233],"well":[232],"leads":[236],"us":[237],"believe":[239],"an":[250],"equally":[251],"manner.":[253],"effectiveness":[255],"universality":[257],"results":[260],"suggests":[261],"combining":[263],"next":[269],"evolution":[270],"catpcha":[272],"solving,":[273],"supersedes":[277],"earlier":[283],"works.":[284],"More":[285],"generally,":[286],"raises":[289],"questions":[290],"about":[291],"how":[292],"develop":[294],"sufficiently":[295],"secure":[296],"future.":[300]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":21},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":15},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2016-06-24T00:00:00"}
