{"id":"https://openalex.org/W7225203447","doi":"https://doi.org/10.1080/1206212x.2026.2759138","title":"LSVB-Net: a statistically motivated deep steganalysis framework based on local statistical variance modeling","display_name":"LSVB-Net: a statistically motivated deep steganalysis framework based on local statistical variance modeling","publication_year":2026,"publication_date":"2026-11-03","ids":{"openalex":"https://openalex.org/W7225203447","doi":"https://doi.org/10.1080/1206212x.2026.2759138"},"language":"en","primary_location":{"id":"doi:10.1080/1206212x.2026.2759138","doi":"https://doi.org/10.1080/1206212x.2026.2759138","is_oa":false,"landing_page_url":"https://doi.org/10.1080/1206212x.2026.2759138","pdf_url":null,"source":{"id":"https://openalex.org/S87797848","display_name":"International Journal of Computers and Applications","issn_l":"1206-212X","issn":["1206-212X","1925-7074"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computers and Applications","raw_type":"journal-article"},"volume":null,"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/A5091412347","display_name":"Bisma Bashir","orcid":"https://orcid.org/0009-0002-5567-0821","observed_orcids":["https://orcid.org/0009-0002-5567-0821"]},"institutions":[{"id":"https://openalex.org/I8778637","display_name":"National Institute of Technology Srinagar","ror":"https://ror.org/03sfwvw54","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210152752","https://openalex.org/I8778637"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Bisma Bashir","raw_affiliation_strings":["National Institute of Technology Srinagar"],"raw_orcid":"https://orcid.org/0009-0002-5567-0821","affiliations":[{"raw_affiliation_string":"National Institute of Technology Srinagar","institution_ids":["https://openalex.org/I8778637"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074385184","display_name":"Roohie Naaz Mir","orcid":"https://orcid.org/0000-0002-6460-0684","observed_orcids":["https://orcid.org/0000-0002-6460-0684"]},"institutions":[{"id":"https://openalex.org/I8778637","display_name":"National Institute of Technology Srinagar","ror":"https://ror.org/03sfwvw54","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210152752","https://openalex.org/I8778637"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Roohie Naaz Mir","raw_affiliation_strings":["National Institute of Technology Srinagar"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology Srinagar","institution_ids":["https://openalex.org/I8778637"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032740203","display_name":"Shaima Qureshi","orcid":"https://orcid.org/0000-0003-4603-1809","observed_orcids":["https://orcid.org/0000-0003-4603-1809"]},"institutions":[{"id":"https://openalex.org/I8778637","display_name":"National Institute of Technology Srinagar","ror":"https://ror.org/03sfwvw54","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210152752","https://openalex.org/I8778637"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shaima Qureshi","raw_affiliation_strings":["National Institute of Technology Srinagar"],"raw_orcid":"https://orcid.org/0000-0003-4603-1809","affiliations":[{"raw_affiliation_string":"National Institute of Technology Srinagar","institution_ids":["https://openalex.org/I8778637"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5091412347"],"corresponding_institution_ids":["https://openalex.org/I8778637"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.80760578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.8794000148773193,"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":0.8794000148773193,"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":0.11240000277757645,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.0017000000225380063,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/image-steganalysis","display_name":"image steganalysis","score":0.996999979019165},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.7319999933242798},{"id":"https://openalex.org/keywords/bossbase","display_name":"BOSSbase","score":0.5550000071525574},{"id":"https://openalex.org/keywords/s-uniward","display_name":"S-UNIWARD","score":0.7409999966621399},{"id":"https://openalex.org/keywords/wow","display_name":"WOW","score":0.6370000243186951},{"id":"https://openalex.org/keywords/hills","display_name":"hills","score":0.9470000267028809}],"concepts":[{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.9671000242233276},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8101000189781189},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6929000020027161},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6739000082015991},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6617000102996826},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.5752999782562256},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5432000160217285},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5428000092506409},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5169000029563904},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.503600001335144},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4699999988079071},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.4325000047683716},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.41359999775886536},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4016999900341034},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.382999986410141},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3659000098705292},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.34599998593330383},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34220001101493835},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C3073032","wikidata":"https://www.wikidata.org/wiki/Q15912075","display_name":"Information hiding","level":3,"score":0.2754000127315521},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.2583000063896179}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/1206212x.2026.2759138","doi":"https://doi.org/10.1080/1206212x.2026.2759138","is_oa":false,"landing_page_url":"https://doi.org/10.1080/1206212x.2026.2759138","pdf_url":null,"source":{"id":"https://openalex.org/S87797848","display_name":"International Journal of Computers and Applications","issn_l":"1206-212X","issn":["1206-212X","1925-7074"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computers and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2009130368","https://openalex.org/W2085924571","https://openalex.org/W2124664712","https://openalex.org/W2170311913","https://openalex.org/W2192227561","https://openalex.org/W2322622188","https://openalex.org/W2538511122","https://openalex.org/W2621048556","https://openalex.org/W2892948265","https://openalex.org/W2913199452","https://openalex.org/W2931088924","https://openalex.org/W2963957509","https://openalex.org/W3010010079","https://openalex.org/W3124809916","https://openalex.org/W4285218349","https://openalex.org/W4376113158","https://openalex.org/W4387037956","https://openalex.org/W4392520145","https://openalex.org/W4396944578","https://openalex.org/W4399157574","https://openalex.org/W4404704192","https://openalex.org/W4408841827","https://openalex.org/W4413381934"],"related_works":["https://openalex.org/W7220866534","https://openalex.org/W2917657850","https://openalex.org/W7172528841","https://openalex.org/W2046180645","https://openalex.org/W4225274170","https://openalex.org/W7161635770","https://openalex.org/W7138390627","https://openalex.org/W7171731133","https://openalex.org/W4387671670","https://openalex.org/W3111851281"],"abstract_inverted_index":{"Image":[0],"steganalysis":[1,12,187],"aims":[2],"to":[3],"detect":[4],"hidden":[5],"information":[6],"embedded":[7],"within":[8],"digital":[9],"images.":[10],"Classical":[11],"methods":[13],"typically":[14],"rely":[15],"on":[16,97],"human":[17],"expertise":[18],"by":[19,180],"crafting":[20],"statistical":[21,41,62,141,186],"features":[22],"from":[23],"residuals,":[24],"whereas":[25],"modern":[26],"deep":[27,55,190],"learning":[28,56],"approaches":[29],"often":[30,38],"treat":[31],"it":[32],"as":[33,93],"a":[34,53,65,145,154,176],"standard":[35],"classification":[36],"problem,":[37],"neglecting":[39],"the":[40,98,116,139,149,162,182],"fingerprints":[42],"of":[43,109,148,175],"steganographic":[44],"embedding.":[45],"To":[46],"address":[47],"this":[48,50],"limitation,":[49],"paper":[51],"introduces":[52],"statistically-motivated":[54],"framework":[57],"that":[58,115,138],"explicitly":[59],"incorporates":[60],"localized":[61],"modeling":[63,143],"into":[64],"convolutional":[66],"neural":[67],"network":[68],"(CNN).":[69],"The":[70,133,166],"proposed":[71,117],"Local":[72],"Statistical":[73],"Variance":[74],"Block":[75],"(LSVB)":[76],"computes":[77],"patch-wise":[78],"variance":[79,142],"mappings":[80],"over":[81,161],"intermediate":[82],"residual":[83,164],"feature":[84],"representations":[85],"using":[86,101],"fixed":[87],"Spatial":[88],"Rich":[89],"Model":[90],"(SRM)":[91],"residuals":[92],"input.":[94],"Extensive":[95],"experiments":[96],"BOSSbase":[99],"dataset":[100],"S-UNIWARD,":[102],"WOW,":[103],"HILL":[104],"and":[105,111,126,172,188],"MiPOD":[106],"at":[107],"payloads":[108],"0.2":[110],"0.4":[112],"bpp":[113],"demonstrate":[114],"technique":[118],"achieves":[119],"comparable":[120],"detection":[121,173],"performance,":[122],"consistently":[123],"outperforming":[124],"Xu-Net":[125],"Yedroudj-Net,":[127],"while":[128],"remaining":[129],"competitive":[130],"with":[131],"GBRAS-Net.":[132],"ablation":[134],"study":[135],"further":[136],"validates":[137],"local":[140],"is":[144],"major":[146],"source":[147],"reported":[150],"performance":[151],"gains,":[152],"yielding":[153],"12.42":[155],"percentage-point":[156],"improvement":[157],"in":[158],"test":[159],"accuracy":[160,174],"baseline":[163],"CNN.":[165],"suggested":[167],"paradigm":[168],"offers":[169],"better":[170],"interpretability":[171],"spatial-domain":[177],"image":[178],"steganalysis,":[179],"bridging":[181],"gap":[183],"between":[184],"traditional":[185],"contemporary":[189],"learning.":[191]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-11-04T00:00:00"}
