{"id":"https://openalex.org/W4387143821","doi":"https://doi.org/10.1145/3613330.3613346","title":"Cybersecurity Named Entity Recognition Based on Word-level Enhancement and Multi-task Learning","display_name":"Cybersecurity Named Entity Recognition Based on Word-level Enhancement and Multi-task Learning","publication_year":2023,"publication_date":"2023-07-27","ids":{"openalex":"https://openalex.org/W4387143821","doi":"https://doi.org/10.1145/3613330.3613346"},"language":"en","primary_location":{"id":"doi:10.1145/3613330.3613346","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3613330.3613346","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Deep Learning Technologies","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/A5088104938","display_name":"Yiqin Lu","orcid":"https://orcid.org/0000-0002-5631-6413"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yiqin Lu","raw_affiliation_strings":["School of Electronic and Information, South China University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, South China University of Technology, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011660116","display_name":"Hong Qi","orcid":"https://orcid.org/0009-0001-3582-2659"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Qi","raw_affiliation_strings":["School of Electronic and Information, South China University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, South China University of Technology, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043385175","display_name":"Jiancheng Qin","orcid":"https://orcid.org/0000-0002-3763-458X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiancheng Qin","raw_affiliation_strings":["School of Electronic and Information, South China University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, South China University of Technology, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050954251","display_name":"Jiarui Chen","orcid":"https://orcid.org/0000-0001-8449-2847"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiarui Chen","raw_affiliation_strings":["School of Electronic and Information, South China University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, South China University of Technology, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102815834","display_name":"Weiqiang Pan","orcid":"https://orcid.org/0009-0006-5091-4582"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiqiang Pan","raw_affiliation_strings":["School of Electronic and Information, South China University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, South China University of Technology, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088104938"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.3479,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66333447,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"71","last_page":"78"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9936000108718872,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9936000108718872,"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"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9901999831199646,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9793999791145325,"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":0.8492074012756348},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.7644706964492798},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.7462957501411438},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.6874306201934814},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6267430186271667},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6208187341690063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5547934174537659},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5068603157997131},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48866894841194153},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.47500598430633545},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.4528459310531616},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4384388327598572},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2893773913383484},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.205277681350708},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0789044201374054}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8492074012756348},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.7644706964492798},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.7462957501411438},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6874306201934814},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6267430186271667},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6208187341690063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5547934174537659},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5068603157997131},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48866894841194153},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.47500598430633545},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.4528459310531616},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4384388327598572},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2893773913383484},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.205277681350708},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0789044201374054},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3613330.3613346","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3613330.3613346","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Deep Learning Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1940872118","https://openalex.org/W2064675550","https://openalex.org/W2890459330","https://openalex.org/W2912691650","https://openalex.org/W2921291646","https://openalex.org/W2938830017","https://openalex.org/W3011594683","https://openalex.org/W3021121749","https://openalex.org/W3098727690","https://openalex.org/W3122890974","https://openalex.org/W3198333480","https://openalex.org/W3199141370","https://openalex.org/W4200046541","https://openalex.org/W4291700196"],"related_works":["https://openalex.org/W2946409105","https://openalex.org/W4205454697","https://openalex.org/W2621151902","https://openalex.org/W3152932816","https://openalex.org/W2985392712","https://openalex.org/W4388996947","https://openalex.org/W3133567596","https://openalex.org/W2798009317","https://openalex.org/W3203949288","https://openalex.org/W4382201653"],"abstract_inverted_index":{"At":[0,202],"present,":[1],"the":[2,11,19,36,47,52,55,61,66,74,78,86,115,124,133,138,149,160,164,168,172,176,185,191,197,203,212,221,224,231,237,242,251],"situation":[3],"of":[4,13,21,32,39,49,54,76,88,151,199,216,223,227],"cybersecurity":[5,22,28,50,101,139,239],"is":[6,23,31,44,82,143,188,208,234],"becoming":[7],"increasingly":[8],"serious,":[9],"and":[10,51,71,108,175,194,241],"study":[12,43],"Named":[14],"Entity":[15],"Recognition":[16],"(NER)":[17],"in":[18,46,73,90,163],"field":[20,75],"helpful":[24],"to":[25,60,84,131,170,210,219],"automatically":[26],"extract":[27],"entities.":[29],"It":[30],"great":[33],"significance":[34],"for":[35,65],"subsequent":[37],"analysis":[38],"cybersecurity.":[40],"However,":[41],"less":[42],"done":[45],"area":[48],"majority":[53],"current":[56],"research":[57],"only":[58],"applies":[59],"general":[62],"field.":[63],"And":[64,148],"dataset":[67],"mixed":[68],"with":[69],"Chinese":[70],"English":[72],"cybersecurity,":[77],"existing":[79],"NER":[80,102,173,192],"method":[81],"difficult":[83],"solve":[85,94],"problem":[87],"ambiguity":[89],"word":[91,134,140],"boundaries.":[92],"To":[93],"this":[95,97,183],"problem,":[96],"paper":[98],"proposes":[99],"a":[100],"model":[103,169,233,253],"based":[104],"on":[105,111,236],"word-level":[106],"enhancement":[107],"multi-task":[109,200,228],"learning":[110],"BERT-BiLSTM-Att-CRF":[112],"(MTLWE).":[113],"One":[114],"one":[116],"hand,":[117,162],"MTLWE":[118,232,252],"obtains":[119],"character-level":[120],"feature":[121,136,157],"vectors":[122,154],"through":[123],"BERT":[125],"pre-trained":[126],"language":[127],"model.":[128],"In":[129,182],"order":[130],"strengthen":[132],"boundary":[135],"information,":[137],"embedding":[141],"vector":[142],"obtained":[144],"by":[145],"Word2Vec":[146],"algorithm.":[147],"combination":[150],"these":[152],"two":[153],"can":[155],"enhance":[156],"information.":[158],"On":[159],"other":[161,258],"model,":[165],"we":[166],"configure":[167],"train":[171],"task":[174,180,193,218],"Word":[177],"Segmentation":[178],"(WS)":[179],"alternately.":[181],"way,":[184],"WS":[186,217],"information":[187,215],"fused":[189],"into":[190],"it":[195],"produces":[196],"impact":[198],"learning.":[201,229],"same":[204],"time,":[205],"adversarial":[206],"training":[207],"used":[209],"filter":[211],"private":[213],"independent":[214],"ensure":[220],"purity":[222],"common":[225],"features":[226],"Finally,":[230],"experimented":[235],"constructed":[238],"dataset,":[240],"F1":[243],"value":[244],"reaches":[245],"65.22%.":[246],"The":[247],"results":[248],"show":[249],"that":[250],"shows":[254],"better":[255],"performance":[256],"than":[257],"baseline":[259],"models.":[260]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
