{"id":"https://openalex.org/W4386471798","doi":"https://doi.org/10.1186/s42400-023-00183-8","title":"Use of subword tokenization for domain generation algorithm classification","display_name":"Use of subword tokenization for domain generation algorithm classification","publication_year":2023,"publication_date":"2023-09-07","ids":{"openalex":"https://openalex.org/W4386471798","doi":"https://doi.org/10.1186/s42400-023-00183-8"},"language":"en","primary_location":{"id":"doi:10.1186/s42400-023-00183-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-023-00183-8","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-023-00183-8","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-023-00183-8","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034962654","display_name":"Sea Ran Cleon Liew","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Sea Ran Cleon Liew","raw_affiliation_strings":["University of Waterloo, Waterloo, Canada"],"affiliations":[{"raw_affiliation_string":"University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016890310","display_name":"Ngai-Fong Law","orcid":"https://orcid.org/0000-0002-9809-5110"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ngai Fong Law","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034962654"],"corresponding_institution_ids":["https://openalex.org/I151746483"],"apc_list":null,"apc_paid":null,"fwci":1.9365,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.88877049,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.9994999766349792,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9988999962806702,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9957000017166138,"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/lexical-analysis","display_name":"Lexical analysis","score":0.7973565459251404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7819639444351196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6361383199691772},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5577568411827087},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.551476776599884},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5434338450431824},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4521399736404419},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4232785403728485},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34521347284317017},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34101414680480957},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07781803607940674}],"concepts":[{"id":"https://openalex.org/C176982825","wikidata":"https://www.wikidata.org/wiki/Q835922","display_name":"Lexical analysis","level":2,"score":0.7973565459251404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7819639444351196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6361383199691772},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5577568411827087},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.551476776599884},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5434338450431824},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4521399736404419},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4232785403728485},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34521347284317017},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34101414680480957},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07781803607940674},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1186/s42400-023-00183-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-023-00183-8","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-023-00183-8","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/107701","is_oa":true,"landing_page_url":"http://hdl.handle.net/10397/107701","pdf_url":"http://ira.lib.polyu.edu.hk/bitstream/10397/107701/1/s42400-023-00183-8.pdf","source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal/Magazine Article"},{"id":"pmh:oai:doaj.org/article:268ad77d30b84924bc96ca004d72d5e0","is_oa":true,"landing_page_url":"https://doaj.org/article/268ad77d30b84924bc96ca004d72d5e0","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Cybersecurity, Vol 6, Iss 1, Pp 1-12 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s42400-023-00183-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-023-00183-8","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-023-00183-8","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4386471798.pdf"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W2082550445","https://openalex.org/W2212753744","https://openalex.org/W2752533296","https://openalex.org/W2773270814","https://openalex.org/W2773671123","https://openalex.org/W2941262352","https://openalex.org/W2977310947","https://openalex.org/W2979462950","https://openalex.org/W2999697944","https://openalex.org/W3011860454","https://openalex.org/W3011866104","https://openalex.org/W3012476877","https://openalex.org/W3014018380","https://openalex.org/W3093591484","https://openalex.org/W3114681532","https://openalex.org/W3172400541","https://openalex.org/W3198971113","https://openalex.org/W4213109153","https://openalex.org/W4214888010","https://openalex.org/W4225070666","https://openalex.org/W4225795409","https://openalex.org/W4285496318"],"related_works":["https://openalex.org/W4386014872","https://openalex.org/W4361193986","https://openalex.org/W1847536016","https://openalex.org/W3149094754","https://openalex.org/W3172681236","https://openalex.org/W2148703997","https://openalex.org/W4366851046","https://openalex.org/W4380568733","https://openalex.org/W2033371749","https://openalex.org/W3214032513"],"abstract_inverted_index":{"Abstract":[0],"Domain":[1],"name":[2],"generation":[3],"algorithm":[4],"(DGA)":[5],"classification":[6,65,89,108],"is":[7,72],"an":[8,98,103],"essential":[9],"but":[10],"challenging":[11],"problem.":[12],"Both":[13],"feature-extracting":[14],"machine":[15],"learning":[16,21],"(ML)":[17],"methods":[18,53],"and":[19,29,125,128],"deep":[20],"(DL)":[22],"models":[23],"such":[24],"as":[25],"convolutional":[26],"neural":[27],"networks":[28],"long":[30],"short-term":[31],"memory":[32],"have":[33],"been":[34],"developed.":[35],"However,":[36],"the":[37,51,64,75,83,92,111,114,119,130],"performance":[38,66,90],"of":[39,46,113],"these":[40],"approaches":[41],"varies":[42],"with":[43],"different":[44],"types":[45],"DGAs.":[47,61,94,115],"Most":[48],"features":[49],"in":[50],"ML":[52,124],"can":[54,86],"characterize":[55],"random-looking":[56],"DGAs":[57],"better":[58],"than":[59],"word-looking":[60,68,93],"To":[62],"improve":[63],"on":[67,91,110],"DGAs,":[69],"subword":[70,84,131],"tokenization":[71,85],"employed":[73],"for":[74,106],"DL":[76,126,132],"models.":[77],"Our":[78],"experimental":[79],"results":[80],"proved":[81],"that":[82,101,118],"provide":[87],"excellent":[88],"We":[95],"then":[96],"propose":[97],"integrated":[99,120],"scheme":[100,121],"chooses":[102],"appropriate":[104],"method":[105],"DGA":[107],"depending":[109],"nature":[112],"Results":[116],"show":[117],"outperformed":[122],"existing":[123],"methods,":[127],"also":[129],"methods.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}