{"id":"https://openalex.org/W2885376490","doi":"https://doi.org/10.1109/icc.2018.8422243","title":"GENPass: A General Deep Learning Model for Password Guessing with PCFG Rules and Adversarial Generation","display_name":"GENPass: A General Deep Learning Model for Password Guessing with PCFG Rules and Adversarial Generation","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2885376490","doi":"https://doi.org/10.1109/icc.2018.8422243","mag":"2885376490"},"language":"en","primary_location":{"id":"doi:10.1109/icc.2018.8422243","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2018.8422243","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5065908408","display_name":"Yunyu Liu","orcid":"https://orcid.org/0000-0002-1539-7050"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunyu Liu","raw_affiliation_strings":["Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009746943","display_name":"Zhiyang Xia","orcid":"https://orcid.org/0000-0002-4708-8260"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyang Xia","raw_affiliation_strings":["Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100709379","display_name":"Ping Yi","orcid":"https://orcid.org/0000-0003-4530-5118"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Yi","raw_affiliation_strings":["Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389420","display_name":"Yao Yao","orcid":"https://orcid.org/0000-0002-0626-3587"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yao Yao","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051057976","display_name":"Tiantian Xie","orcid":"https://orcid.org/0000-0002-4790-925X"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tiantian Xie","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100392263","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0003-3240-1485"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101496983","display_name":"Ting Zhu","orcid":"https://orcid.org/0000-0003-3307-050X"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ting Zhu","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of-Maryland, Baltimore County, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5065908408"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":7.0684,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.97178131,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11800","display_name":"User Authentication and Security Systems","score":1.0,"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":1.0,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9789999723434448,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8468421101570129},{"id":"https://openalex.org/keywords/password","display_name":"Password","score":0.7534523010253906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6081191301345825},{"id":"https://openalex.org/keywords/password-cracking","display_name":"Password cracking","score":0.5623898506164551},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5430009961128235},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5352585315704346},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4885212182998657},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4795607924461365},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4471113681793213},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4396519660949707},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4390292167663574},{"id":"https://openalex.org/keywords/dictionary-attack","display_name":"Dictionary attack","score":0.43633610010147095},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.41956669092178345},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.41899406909942627},{"id":"https://openalex.org/keywords/password-strength","display_name":"Password strength","score":0.3031849265098572},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.13151901960372925},{"id":"https://openalex.org/keywords/one-time-password","display_name":"One-time password","score":0.12137079238891602},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08725166320800781}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8468421101570129},{"id":"https://openalex.org/C109297577","wikidata":"https://www.wikidata.org/wiki/Q161157","display_name":"Password","level":2,"score":0.7534523010253906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6081191301345825},{"id":"https://openalex.org/C3847113","wikidata":"https://www.wikidata.org/wiki/Q2746524","display_name":"Password cracking","level":5,"score":0.5623898506164551},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5430009961128235},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5352585315704346},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4885212182998657},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4795607924461365},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4471113681793213},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4396519660949707},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4390292167663574},{"id":"https://openalex.org/C113328881","wikidata":"https://www.wikidata.org/wiki/Q599809","display_name":"Dictionary attack","level":3,"score":0.43633610010147095},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.41956669092178345},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.41899406909942627},{"id":"https://openalex.org/C70530487","wikidata":"https://www.wikidata.org/wiki/Q1990841","display_name":"Password strength","level":4,"score":0.3031849265098572},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.13151901960372925},{"id":"https://openalex.org/C89479133","wikidata":"https://www.wikidata.org/wiki/Q1137840","display_name":"One-time password","level":3,"score":0.12137079238891602},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08725166320800781},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc.2018.8422243","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2018.8422243","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5799999833106995}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W324839447","https://openalex.org/W942441284","https://openalex.org/W1598796236","https://openalex.org/W1607198972","https://openalex.org/W1810943226","https://openalex.org/W1969911795","https://openalex.org/W1977652969","https://openalex.org/W2007488200","https://openalex.org/W2007659052","https://openalex.org/W2058516911","https://openalex.org/W2073103209","https://openalex.org/W2086553822","https://openalex.org/W2099471712","https://openalex.org/W2102551539","https://openalex.org/W2119856652","https://openalex.org/W2135359429","https://openalex.org/W2170240176","https://openalex.org/W2174113119","https://openalex.org/W2257979135","https://openalex.org/W2289410981","https://openalex.org/W2396652220","https://openalex.org/W2404004865","https://openalex.org/W2463456957","https://openalex.org/W2490171383","https://openalex.org/W2538793708","https://openalex.org/W2538833168","https://openalex.org/W2963012544","https://openalex.org/W2963532563","https://openalex.org/W3148312535","https://openalex.org/W4285719527","https://openalex.org/W4320013936","https://openalex.org/W4321320097","https://openalex.org/W6638273328","https://openalex.org/W6685117906","https://openalex.org/W6696687478","https://openalex.org/W6711768119","https://openalex.org/W6713444845","https://openalex.org/W6719406283"],"related_works":["https://openalex.org/W2213939375","https://openalex.org/W2906808255","https://openalex.org/W2787328792","https://openalex.org/W4319978184","https://openalex.org/W4319158737","https://openalex.org/W2402445170","https://openalex.org/W2187843169","https://openalex.org/W2187195398","https://openalex.org/W3131491961","https://openalex.org/W4239831152"],"abstract_inverted_index":{"Password":[0],"has":[1,91],"become":[2],"today's":[3],"dominant":[4],"method":[5],"of":[6,134,143,204,211],"authentication":[7],"in":[8,123,176,216],"social":[9],"network.":[10],"While":[11],"the":[12,21,25,30,118,171,177,201,217],"brute-force":[13],"attack":[14,86],"methods,":[15],"such":[16,36],"as":[17,37],"HashCat":[18],"and":[19,40,67,116,194],"John":[20],"Ripper,":[22],"are":[23,44],"unpractical,":[24],"research":[26],"then":[27],"switches":[28],"to":[29,159,191],"password":[31,70,104,132],"guess.":[32],"The":[33,57,131,197],"state-of-the-art":[34],"approaches,":[35],"Markov":[38],"Model":[39],"probabilistic":[41],"context-free":[42],"grammars(PCFG),":[43],"all":[45],"based":[46],"on":[47,59],"statistical":[48],"probability.":[49],"These":[50],"approaches":[51],"have":[52,62],"a":[53,76,98,141,183],"low":[54],"matching":[55,172,202],"rate.":[56],"methods":[58],"neural":[60,78,149],"network":[61,79,150],"been":[63],"proved":[64],"more":[65],"accurate":[66],"practical":[68],"for":[69,84,103],"guessing":[71],"than":[72,209],"traditional":[73],"methods.":[74],"However,":[75],"raw":[77],"model":[80,102],"is":[81,136,140,206],"not":[82],"qualified":[83],"cross-sites":[85,178,218],"since":[87],"each":[88],"data":[89,114,125],"set":[90,160],"its":[92],"own":[93],"features.":[94],"This":[95],"paper":[96],"proposes":[97],"general":[99],"deep":[100],"learning":[101,181],"guessing,":[105],"called":[106],"GENPass.":[107],"GENPass":[108,135,186,205],"can":[109],"learn":[110,192],"features":[111],"from":[112,182],"several":[113,188],"sets":[115,126],"ensure":[117],"output":[119],"wordlist":[120],"high":[121],"accuracy":[122],"different":[124],"by":[127,174],"using":[128],"adversarial":[129],"generation.":[130],"generator":[133],"PCFG+LSTM(PL),":[137],"where":[138],"LSTM":[139],"kind":[142],"Recurrent":[144],"Neural":[145],"Network.":[146],"We":[147],"combine":[148],"with":[151,163,167],"PCFG":[152],"because":[153],"we":[154],"found":[155],"people":[156],"were":[157],"used":[158],"their":[161],"passwords":[162],"meaningful":[164],"strings.":[165],"Compared":[166],"LSTM,":[168],"PL":[169,189],"increased":[170],"rate":[173,203],"16%-30%":[175],"tests":[179],"when":[180],"single":[184],"dataset.":[185],"uses":[187],"models":[190],"datasets":[193,215],"generate":[195],"passwords.":[196],"result":[198],"shows":[199],"that":[200,210],"20%":[207],"higher":[208],"simply":[212],"mixing":[213],"those":[214],"test.":[219]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
