{"id":"https://openalex.org/W3015534721","doi":"https://doi.org/10.1109/icassp40776.2020.9053670","title":"Texception: A Character/Word-Level Deep Learning Model for Phishing URL Detection","display_name":"Texception: A Character/Word-Level Deep Learning Model for Phishing URL Detection","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015534721","doi":"https://doi.org/10.1109/icassp40776.2020.9053670","mag":"3015534721"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5061108898","display_name":"Farid Tajaddodianfar","orcid":"https://orcid.org/0000-0002-6135-1993"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Farid Tajaddodianfar","raw_affiliation_strings":["Microsoft Corporation, One Microsoft Way, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, One Microsoft Way, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059859993","display_name":"Jack W. Stokes","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jack W. Stokes","raw_affiliation_strings":["Microsoft Corporation, One Microsoft Way, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, One Microsoft Way, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088331085","display_name":"Arun Gururajan","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arun Gururajan","raw_affiliation_strings":["Microsoft Corporation, One Microsoft Way, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, One Microsoft Way, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061108898"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":12.0106,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.98549558,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2857","last_page":"2861"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","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/T11644","display_name":"Spam and Phishing Detection","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/T11147","display_name":"Misinformation and Its Impacts","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9980000257492065,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/phishing","display_name":"Phishing","score":0.8400942087173462},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8361116647720337},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.619988203048706},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.5624959468841553},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.5326295495033264},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.5287905335426331},{"id":"https://openalex.org/keywords/confidentiality","display_name":"Confidentiality","score":0.49261361360549927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45173391699790955},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45119142532348633},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43345725536346436},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4311378598213196},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.396171510219574},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.35343846678733826},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.19112828373908997}],"concepts":[{"id":"https://openalex.org/C83860907","wikidata":"https://www.wikidata.org/wiki/Q135005","display_name":"Phishing","level":3,"score":0.8400942087173462},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8361116647720337},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.619988203048706},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.5624959468841553},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.5326295495033264},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.5287905335426331},{"id":"https://openalex.org/C71745522","wikidata":"https://www.wikidata.org/wiki/Q2476929","display_name":"Confidentiality","level":2,"score":0.49261361360549927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45173391699790955},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45119142532348633},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43345725536346436},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4311378598213196},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.396171510219574},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.35343846678733826},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.19112828373908997},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W168564468","https://openalex.org/W1775434803","https://openalex.org/W2028223155","https://openalex.org/W2097117768","https://openalex.org/W2109255472","https://openalex.org/W2153579005","https://openalex.org/W2493916176","https://openalex.org/W2580641941","https://openalex.org/W2787538540","https://openalex.org/W2899771611","https://openalex.org/W2945960282","https://openalex.org/W2963626623","https://openalex.org/W2964046515","https://openalex.org/W4294170691","https://openalex.org/W6606906144","https://openalex.org/W6637845829","https://openalex.org/W6682691769","https://openalex.org/W6732691979","https://openalex.org/W6748384357","https://openalex.org/W6756040250"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W2968295315","https://openalex.org/W3034267371"],"abstract_inverted_index":{"Phishing":[0],"is":[1,136,163],"the":[2,10,28,38,41,79,148],"starting":[3],"point":[4],"for":[5,125,165],"many":[6],"cyberattacks":[7],"that":[8,26,55,117,134],"threaten":[9],"confidentiality,":[11],"availability":[12],"and":[13,17,61,75,82,109],"integrity":[14],"of":[15,22,34,40],"enterprises'":[16],"consumers'":[18],"data.":[19],"The":[20],"URL":[21,58,81],"a":[23,31,49,57,67,141],"web":[24,42],"page":[25],"hosts":[27],"attack":[29],"provides":[30],"rich":[32],"source":[33],"information":[35,77],"to":[36,66,122,138],"determine":[37],"maliciousness":[39],"server.":[43],"In":[44,100],"this":[45,118],"work,":[46],"we":[47],"propose":[48],"novel":[50],"deep":[51],"learning":[52],"architecture,":[53],"Texception,":[54],"takes":[56],"as":[59],"input":[60],"predicts":[62],"whether":[63],"it":[64,95],"belongs":[65],"phishing":[68],"attack.":[69],"Architecturally,":[70],"Texception":[71,102,121,135],"uses":[72],"both":[73],"character-level":[74],"word-level":[76],"from":[78,97,104],"incoming":[80],"does":[83],"not":[84],"depend":[85],"on":[86,130],"manually":[87],"crafted":[88],"features":[89],"or":[90,113],"feature":[91],"engineering.":[92],"This":[93],"makes":[94],"different":[96],"classical":[98],"approaches.":[99],"addition,":[101],"benefits":[103],"multiple":[105],"parallel":[106],"convolutional":[107],"layers":[108],"can":[110],"grow":[111],"deeper":[112],"wider.":[114],"We":[115],"show":[116,133],"flexibility":[119],"enables":[120],"generalize":[123],"better":[124],"new":[126],"URLs.":[127],"Our":[128],"results":[129],"production":[131],"data":[132],"able":[137],"significantly":[139],"outperform":[140],"traditional":[142],"text":[143],"classification":[144],"method":[145],"by":[146,152],"increasing":[147],"true":[149],"positive":[150,159],"rate":[151,160],"126.7%":[153],"at":[154,170],"an":[155],"extremely":[156],"low":[157],"false":[158],"(0.01%)":[161],"which":[162],"crucial":[164],"our":[166],"model's":[167],"healthy":[168],"operation":[169],"internet":[171],"scale.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":23},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}