{"id":"https://openalex.org/W4387272267","doi":"https://doi.org/10.1109/taslp.2023.3319975","title":"Text Steganalysis Based on Hierarchical Supervised Learning and Dual Attention Mechanism","display_name":"Text Steganalysis Based on Hierarchical Supervised Learning and Dual Attention Mechanism","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387272267","doi":"https://doi.org/10.1109/taslp.2023.3319975"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2023.3319975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2023.3319975","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-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/A5084672117","display_name":"Wanli Peng","orcid":"https://orcid.org/0000-0001-9636-6928"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanli Peng","raw_affiliation_strings":["School of Computer Science and Key Laboratory of Culture & Tourism Intelligent Computing of Ministry of Culture & Tourism, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-9636-6928","affiliations":[{"raw_affiliation_string":"School of Computer Science and Key Laboratory of Culture & Tourism Intelligent Computing of Ministry of Culture & Tourism, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359820","display_name":"Sheng Li","orcid":"https://orcid.org/0000-0002-7589-9554"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Li","raw_affiliation_strings":["School of Computer Science and Key Laboratory of Culture & Tourism Intelligent Computing of Ministry of Culture & Tourism, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-7589-9554","affiliations":[{"raw_affiliation_string":"School of Computer Science and Key Laboratory of Culture & Tourism Intelligent Computing of Ministry of Culture & Tourism, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054324316","display_name":"Zhenxing Qian","orcid":"https://orcid.org/0000-0003-1622-0561"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenxing Qian","raw_affiliation_strings":["School of Computer Science and Key Laboratory of Culture & Tourism Intelligent Computing of Ministry of Culture & Tourism, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-1622-0561","affiliations":[{"raw_affiliation_string":"School of Computer Science and Key Laboratory of Culture & Tourism Intelligent Computing of Ministry of Culture & Tourism, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101889358","display_name":"Xinpeng Zhang","orcid":"https://orcid.org/0000-0002-0212-3501"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinpeng Zhang","raw_affiliation_strings":["School of Computer Science and Key Laboratory of Culture & Tourism Intelligent Computing of Ministry of Culture & Tourism, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-0212-3501","affiliations":[{"raw_affiliation_string":"School of Computer Science and Key Laboratory of Culture & Tourism Intelligent Computing of Ministry of Culture & Tourism, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2456,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.9018098,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"31","issue":null,"first_page":"3513","last_page":"3526"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9998999834060669,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9998999834060669,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9980999827384949,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9958999752998352,"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/steganalysis","display_name":"Steganalysis","score":0.9642630219459534},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7613039016723633},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7567160725593567},{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.7166401743888855},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5737425088882446},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49741533398628235},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44379061460494995},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43212658166885376},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41822510957717896}],"concepts":[{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.9642630219459534},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7613039016723633},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7567160725593567},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.7166401743888855},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5737425088882446},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49741533398628235},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44379061460494995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43212658166885376},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41822510957717896},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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:10.1109/taslp.2023.3319975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2023.3319975","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6600000262260437,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1961232708","display_name":null,"funder_award_id":"U22B2047","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2429589907","display_name":null,"funder_award_id":"U1936214","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2724549297","display_name":null,"funder_award_id":"62072114","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3243374375","display_name":null,"funder_award_id":"2023M730646","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G3935748781","display_name":null,"funder_award_id":"U20A20178","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6435596466","display_name":null,"funder_award_id":"U20B2051","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1504425755","https://openalex.org/W1554043606","https://openalex.org/W1565070293","https://openalex.org/W1574901103","https://openalex.org/W1830858140","https://openalex.org/W1875842236","https://openalex.org/W1965997238","https://openalex.org/W2018576906","https://openalex.org/W2048305092","https://openalex.org/W2069994443","https://openalex.org/W2089798121","https://openalex.org/W2123170991","https://openalex.org/W2139842737","https://openalex.org/W2313876608","https://openalex.org/W2618218947","https://openalex.org/W2735673012","https://openalex.org/W2888048838","https://openalex.org/W2893556909","https://openalex.org/W2896457183","https://openalex.org/W2900236614","https://openalex.org/W2911759304","https://openalex.org/W2912142077","https://openalex.org/W2920628035","https://openalex.org/W2941326838","https://openalex.org/W2947752314","https://openalex.org/W2950729339","https://openalex.org/W2952265495","https://openalex.org/W2963444877","https://openalex.org/W2963446712","https://openalex.org/W2970641574","https://openalex.org/W2971140743","https://openalex.org/W2986670728","https://openalex.org/W2990143630","https://openalex.org/W2998457557","https://openalex.org/W3037454483","https://openalex.org/W3085519426","https://openalex.org/W3135748828","https://openalex.org/W3151165339","https://openalex.org/W3162945253","https://openalex.org/W3174512969","https://openalex.org/W3175755605","https://openalex.org/W3187420508","https://openalex.org/W3210326237","https://openalex.org/W3215372840","https://openalex.org/W4200034001","https://openalex.org/W4226391080","https://openalex.org/W4253000688","https://openalex.org/W4283393394","https://openalex.org/W4285171092","https://openalex.org/W4288778377","https://openalex.org/W4312416962","https://openalex.org/W4312911257","https://openalex.org/W4385245566","https://openalex.org/W6638789522","https://openalex.org/W6640963894","https://openalex.org/W6676984168","https://openalex.org/W6737123006","https://openalex.org/W6746523225","https://openalex.org/W6755857782"],"related_works":["https://openalex.org/W2148973528","https://openalex.org/W2939392096","https://openalex.org/W4243922849","https://openalex.org/W2106726851","https://openalex.org/W4309385482","https://openalex.org/W2792878404","https://openalex.org/W2068740952","https://openalex.org/W1583147569","https://openalex.org/W2182496537","https://openalex.org/W3154843532"],"abstract_inverted_index":{"Recent":[0],"methods":[1],"with":[2],"deep":[3,45],"neural":[4],"networks":[5],"for":[6,196],"text":[7,30,34,73,90,173,197,206,217,221,224,228],"steganalysis":[8,35,91,207,218],"have":[9,22],"succeeded":[10],"in":[11,40,55,144],"mining":[12],"various":[13],"feature":[14,193],"representations.":[15],"However,":[16],"a":[17,76,99,115,178],"limited":[18],"number":[19],"of":[20,28,44,71,83,148,159,171],"studies":[21],"explicitly":[23],"analyzed":[24],"potential":[25],"security":[26],"issues":[27],"generative":[29,72,172],"steganography.":[31,174],"Furthermore,":[32],"current":[33,211],"approaches":[36],"lack":[37],"detailed":[38],"consideration":[39],"the":[41,67,110,119,135,145,168,185,210],"intricate":[42],"design":[43],"learning":[46,97,122],"architectures":[47],"tailored":[48],"to":[49,57,104,164],"these":[50,59],"challenges.":[51],"In":[52,81],"this":[53],"article,":[54],"order":[56],"tackle":[58],"problems,":[60],"we":[61,85,176],"first":[62],"theoretically":[63],"and":[64,78,98,140,150,162,187,226],"empirically":[65],"analyze":[66],"inevitable":[68],"embedding":[69],"distortions":[70],"steganography":[74],"at":[75],"semantic":[77,108,186],"statistical":[79,169,188],"levels.":[80],"light":[82],"this,":[84],"then":[86,154],"propose":[87],"an":[88,157],"innovative":[89],"method":[92,112,208],"based":[93],"on":[94,134],"hierarchical":[95,120],"supervised":[96,121],"dual":[100,179],"attention":[101,180],"mechanism.":[102],"Concretely,":[103],"extract":[105],"highly":[106],"effective":[107],"features,":[109,189],"proposed":[111,205],"involves":[113],"fine-tuning":[114],"BERT":[116],"extractor":[117],"through":[118],"that":[123,182,203],"combines":[124],"signals":[125],"from":[126],"multiple":[127],"softmax":[128],"classifiers,":[129],"rather":[130],"than":[131],"relying":[132],"solely":[133],"final":[136],"one.":[137],"The":[138,199],"mean":[139],"standard":[141],"deviation":[142],"values":[143],"Gaussian":[146],"distribution":[147],"cover":[149],"stego":[151],"texts":[152],"are":[153],"estimated":[155],"using":[156],"encoder":[158],"variational":[160],"autoencoders":[161],"used":[163],"capture":[165],"features":[166],"representing":[167],"distortion":[170],"Subsequently,":[175],"introduce":[177],"mechanism":[181],"dynamically":[183],"fuses":[184],"thereby":[190],"creating":[191],"discriminative":[192],"representations":[194],"essential":[195],"steganalysis.":[198,229],"experimental":[200],"results":[201],"demonstrate":[202],"our":[204],"surpasses":[209],"state-of-the-art":[212],"techniques":[213],"across":[214],"three":[215],"distinct":[216],"scenarios:":[219],"specific":[220],"steganalysis,":[222,225],"semi-blind":[223],"blind":[227]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}