{"id":"https://openalex.org/W4206796315","doi":"https://doi.org/10.1109/access.2022.3140342","title":"A Deep Bidirectional LSTM-GRU Network Model for Automated Ciphertext Classification","display_name":"A Deep Bidirectional LSTM-GRU Network Model for Automated Ciphertext Classification","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4206796315","doi":"https://doi.org/10.1109/access.2022.3140342"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3140342","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3140342","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09668927.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09668927.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088268622","display_name":"Ezat Ahmadzadeh","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ezat Ahmadzadeh","raw_affiliation_strings":["DGIST, Hyeonpung-myeon, Daegu, Dalseong-gun, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DGIST, Hyeonpung-myeon, Daegu, Dalseong-gun, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101568462","display_name":"Hyunil Kim","orcid":"https://orcid.org/0000-0002-4018-4540"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunil Kim","raw_affiliation_strings":["DGIST, Hyeonpung-myeon, Daegu, Dalseong-gun, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-4018-4540","affiliations":[{"raw_affiliation_string":"DGIST, Hyeonpung-myeon, Daegu, Dalseong-gun, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022484420","display_name":"Ongee Jeong","orcid":"https://orcid.org/0000-0002-6276-9769"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ongee Jeong","raw_affiliation_strings":["DGIST, Hyeonpung-myeon, Daegu, Dalseong-gun, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-6276-9769","affiliations":[{"raw_affiliation_string":"DGIST, Hyeonpung-myeon, Daegu, Dalseong-gun, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033521823","display_name":"Namki Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Namki Kim","raw_affiliation_strings":["DGIST, Hyeonpung-myeon, Daegu, Dalseong-gun, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DGIST, Hyeonpung-myeon, Daegu, Dalseong-gun, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088864309","display_name":"Inkyu Moon","orcid":"https://orcid.org/0000-0003-0882-8585"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Inkyu Moon","raw_affiliation_strings":["DGIST, Hyeonpung-myeon, Daegu, Dalseong-gun, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-0882-8585","affiliations":[{"raw_affiliation_string":"DGIST, Hyeonpung-myeon, Daegu, Dalseong-gun, South Korea","institution_ids":["https://openalex.org/I193352282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I193352282"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.1931,"has_fulltext":true,"cited_by_count":62,"citation_normalized_percentile":{"value":0.97483509,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"10","issue":null,"first_page":"3228","last_page":"3237"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10951","display_name":"Cryptographic Implementations and Security","score":0.9851999878883362,"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/computer-science","display_name":"Computer science","score":0.8587652444839478},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6748149991035461},{"id":"https://openalex.org/keywords/ciphertext","display_name":"Ciphertext","score":0.656857967376709},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6250249147415161},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5847010612487793},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5479748249053955},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5437023639678955},{"id":"https://openalex.org/keywords/semantic-security","display_name":"Semantic security","score":0.42966213822364807},{"id":"https://openalex.org/keywords/cipher","display_name":"Cipher","score":0.42282137274742126},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4052165746688843},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3653927743434906},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.2795991003513336},{"id":"https://openalex.org/keywords/public-key-cryptography","display_name":"Public-key cryptography","score":0.11281377077102661},{"id":"https://openalex.org/keywords/attribute-based-encryption","display_name":"Attribute-based encryption","score":0.0810440182685852}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8587652444839478},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6748149991035461},{"id":"https://openalex.org/C93974786","wikidata":"https://www.wikidata.org/wiki/Q1589480","display_name":"Ciphertext","level":3,"score":0.656857967376709},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6250249147415161},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5847010612487793},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5479748249053955},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5437023639678955},{"id":"https://openalex.org/C204806902","wikidata":"https://www.wikidata.org/wiki/Q2333581","display_name":"Semantic security","level":5,"score":0.42966213822364807},{"id":"https://openalex.org/C2780221543","wikidata":"https://www.wikidata.org/wiki/Q4681865","display_name":"Cipher","level":3,"score":0.42282137274742126},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4052165746688843},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3653927743434906},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.2795991003513336},{"id":"https://openalex.org/C203062551","wikidata":"https://www.wikidata.org/wiki/Q201339","display_name":"Public-key cryptography","level":3,"score":0.11281377077102661},{"id":"https://openalex.org/C7646194","wikidata":"https://www.wikidata.org/wiki/Q4818713","display_name":"Attribute-based encryption","level":4,"score":0.0810440182685852},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3140342","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3140342","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09668927.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5b97819f86ce437dba9f1515246ec180","is_oa":true,"landing_page_url":"https://doaj.org/article/5b97819f86ce437dba9f1515246ec180","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 3228-3237 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3140342","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3140342","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09668927.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1568234472","display_name":null,"funder_award_id":"2020-0-00126","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G8125359987","display_name":null,"funder_award_id":"2020-0-00126","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4206796315.pdf","grobid_xml":"https://content.openalex.org/works/W4206796315.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1576269089","https://openalex.org/W1971830904","https://openalex.org/W1977378966","https://openalex.org/W1993032872","https://openalex.org/W2014199986","https://openalex.org/W2017964704","https://openalex.org/W2129677775","https://openalex.org/W2583928538","https://openalex.org/W2799476711","https://openalex.org/W2799810798","https://openalex.org/W2911752708","https://openalex.org/W2912639359","https://openalex.org/W2913125146","https://openalex.org/W2919358988","https://openalex.org/W2941716987","https://openalex.org/W2941799245","https://openalex.org/W2962801086","https://openalex.org/W2972178360","https://openalex.org/W2989793668","https://openalex.org/W3005707225","https://openalex.org/W3011541778","https://openalex.org/W3013786767","https://openalex.org/W3014331844","https://openalex.org/W3015829105","https://openalex.org/W3026796362","https://openalex.org/W3028500496","https://openalex.org/W3041856066","https://openalex.org/W3081483437","https://openalex.org/W3087352798","https://openalex.org/W3119282099","https://openalex.org/W3121075225","https://openalex.org/W3124959131","https://openalex.org/W3139241501","https://openalex.org/W3156911071","https://openalex.org/W3174909610","https://openalex.org/W6691661685","https://openalex.org/W6729162402","https://openalex.org/W6748182923","https://openalex.org/W6757270403"],"related_works":["https://openalex.org/W3029058925","https://openalex.org/W2015940479","https://openalex.org/W2096211577","https://openalex.org/W2363701519","https://openalex.org/W2991416436","https://openalex.org/W1589129854","https://openalex.org/W1939781145","https://openalex.org/W2383331906","https://openalex.org/W2355126378","https://openalex.org/W1906282778"],"abstract_inverted_index":{"Long":[0],"Short-Term":[1],"Memory":[2],"(LSTM)":[3],"and":[4,45,106,116],"Gated":[5],"Recurrent":[6,13],"Units":[7],"(GRU)":[8],"are":[9],"a":[10,26,38,58,134],"class":[11],"of":[12,29,138,145],"Neural":[14],"Networks":[15],"(RNN)":[16],"suitable":[17],"for":[18,72,159],"sequential":[19],"data":[20],"processing.":[21],"Bidirectional":[22],"LSTM":[23],"(BLSTM)":[24],"enables":[25],"better":[27],"understanding":[28],"context":[30],"by":[31],"learning":[32],"the":[33,49,78,82,127,143,150,160],"future":[34],"time":[35,152],"steps":[36],"in":[37,48],"bidirectional":[39],"manner.":[40],"Moreover,":[41],"GRU":[42],"deploys":[43],"reset":[44],"update":[46],"gates":[47],"hidden":[50],"layer,":[51],"which":[52,81],"is":[53,149],"computationally":[54],"more":[55],"efficient":[56,65],"than":[57],"conventional":[59],"LSTM.":[60],"This":[61],"paper":[62],"proposes":[63],"an":[64,153],"network":[66,114,131],"model":[67,87,132,155],"based":[68],"on":[69,95],"deep":[70,119],"BLSTM-GRU":[71,128],"ciphertext":[73,83,161],"classification":[74,136],"aiming":[75],"to":[76,80,140],"mark":[77],"category":[79],"belongs.":[84],"The":[85,122],"proposed":[86],"performance":[88,107],"was":[89,108],"evaluated":[90],"using":[91],"well-known":[92],"evaluation":[93],"metrics":[94],"two":[96],"publicly":[97],"available":[98],"datasets":[99],"encrypted":[100],"with":[101],"various":[102,117],"classical":[103],"cipher":[104],"methods":[105],"compared":[109],"against":[110],"one-dimensional":[111],"convolutional":[112],"neural":[113],"(1D-CNN)":[115],"other":[118],"learning-based":[120],"approaches.":[121],"experimental":[123],"results":[124],"showed":[125],"that":[126],"cell":[129],"unit":[130],"achieved":[133],"high":[135],"accuracy":[137],"up":[139],"95.8%.":[141],"To":[142],"best":[144],"our":[146],"knowledge,":[147],"this":[148],"first":[151],"RNN-based":[154],"has":[156],"been":[157],"applied":[158],"classification.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":9}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
