{"id":"https://openalex.org/W4206487993","doi":"https://doi.org/10.1109/bigdata52589.2021.9671531","title":"Convolutional Neural Network Optimization for Phishing Email Classification","display_name":"Convolutional Neural Network Optimization for Phishing Email Classification","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4206487993","doi":"https://doi.org/10.1109/bigdata52589.2021.9671531"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671531","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","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/A5047519702","display_name":"Cameron McGinley","orcid":null},"institutions":[{"id":"https://openalex.org/I39587148","display_name":"Wichita State University","ror":"https://ror.org/00c4e7y75","country_code":"US","type":"education","lineage":["https://openalex.org/I39587148"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Cameron McGinley","raw_affiliation_strings":["School of Computing, Wichita State University, Wichita, Kansas, USA"],"affiliations":[{"raw_affiliation_string":"School of Computing, Wichita State University, Wichita, Kansas, USA","institution_ids":["https://openalex.org/I39587148"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047448225","display_name":"Sergio A. Salinas Monroy","orcid":"https://orcid.org/0000-0001-5545-8826"},"institutions":[{"id":"https://openalex.org/I39587148","display_name":"Wichita State University","ror":"https://ror.org/00c4e7y75","country_code":"US","type":"education","lineage":["https://openalex.org/I39587148"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergio A. Salinas Monroy","raw_affiliation_strings":["School of Computing, Wichita State University, Wichita, Kansas, USA"],"affiliations":[{"raw_affiliation_string":"School of Computing, Wichita State University, Wichita, Kansas, USA","institution_ids":["https://openalex.org/I39587148"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047519702"],"corresponding_institution_ids":["https://openalex.org/I39587148"],"apc_list":null,"apc_paid":null,"fwci":2.5644,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.91183036,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5609","last_page":"5613"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9983000159263611,"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/phishing","display_name":"Phishing","score":0.9160588979721069},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.837885320186615},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.659975528717041},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.5357043147087097},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.46626266837120056},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.45018988847732544},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.4436531662940979},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.39099574089050293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3334447145462036},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.15155643224716187}],"concepts":[{"id":"https://openalex.org/C83860907","wikidata":"https://www.wikidata.org/wiki/Q135005","display_name":"Phishing","level":3,"score":0.9160588979721069},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.837885320186615},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.659975528717041},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.5357043147087097},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.46626266837120056},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.45018988847732544},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.4436531662940979},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.39099574089050293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3334447145462036},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.15155643224716187},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671531","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:soar.wichita.edu:10057/23106","is_oa":false,"landing_page_url":"https://soar.wichita.edu/handle/10057/23106","pdf_url":null,"source":{"id":"https://openalex.org/S4306401479","display_name":"Holmes Museum Of Anthropology (Wichita State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39587148","host_organization_name":"Wichita State University","host_organization_lineage":["https://openalex.org/I39587148"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5600000023841858},{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W50596167","https://openalex.org/W1603920809","https://openalex.org/W1832693441","https://openalex.org/W1904365287","https://openalex.org/W2011211026","https://openalex.org/W2021327598","https://openalex.org/W2095705004","https://openalex.org/W2170240176","https://openalex.org/W2497967381","https://openalex.org/W2532117426","https://openalex.org/W2791521493","https://openalex.org/W2802914762","https://openalex.org/W2803881474","https://openalex.org/W2944103016","https://openalex.org/W3011999700","https://openalex.org/W3012282822","https://openalex.org/W4205947740","https://openalex.org/W6602057100","https://openalex.org/W6636209487","https://openalex.org/W6640036494","https://openalex.org/W6674330103","https://openalex.org/W6685053522","https://openalex.org/W6751397831","https://openalex.org/W6774731884"],"related_works":["https://openalex.org/W2149202530","https://openalex.org/W2807822918","https://openalex.org/W2921723332","https://openalex.org/W2482950156","https://openalex.org/W3042334625","https://openalex.org/W3139248031","https://openalex.org/W4200017362","https://openalex.org/W2911655849","https://openalex.org/W4286432911","https://openalex.org/W3134737443"],"abstract_inverted_index":{"Phishing":[0],"emails":[1,135],"are":[2,51],"one":[3,142],"of":[4,34,82,108,150,153,157],"the":[5,40,80,95,98,109,112,120,123,139],"most":[6],"common":[7],"and":[8,36,64,115,136,155],"effective":[9],"tools":[10,35],"that":[11,42,88,122,138],"cybercriminals":[12,50],"use":[13,31],"to":[14,17,53,71],"gain":[15],"access":[16],"an":[18,106,148],"organization\u2019s":[19],"network":[20,85],"or":[21],"personal":[22],"information.":[23],"To":[24],"detect":[25],"these":[26,55],"attacks,":[27],"email":[28,47,99],"service":[29],"providers":[30],"a":[32,69,117],"variety":[33],"indicators,":[37],"such":[38],"as":[39,104],"URLs":[41,60],"attackers":[43],"include":[44],"in":[45,61,68,97,111],"their":[46,62,73],"messages.":[48,100],"However,":[49],"able":[52],"bypass":[54],"detection":[56],"techniques":[57],"by":[58,92],"omitting":[59],"messages":[63],"instead":[65],"engaging":[66],"victims":[67],"conversation":[70],"advance":[72],"attacks.":[74],"In":[75],"this":[76],"paper,":[77],"we":[78],"investigate":[79],"performance":[81],"convolutional":[83],"neural":[84],"(CNN)":[86],"models":[87,102],"identify":[89,144],"phishing":[90,134,145],"attacks":[91,146],"analyzing":[93],"only":[94],"text":[96,110],"The":[101],"take":[103],"input":[105],"embedding":[107],"email\u2019s":[113],"body":[114],"output":[116],"probability":[118],"indicating":[119],"likelihood":[121],"message":[124],"is":[125],"malicious.":[126],"We":[127],"evaluate":[128],"several":[129],"CNN":[130],"architectures":[131],"using":[132],"real-world":[133],"find":[137],"best":[140],"performing":[141],"can":[143],"with":[147],"accuracy":[149],"98.139%,":[151],"recall":[152],"98.125%,":[154],"precision":[156],"98.269%.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
