{"id":"https://openalex.org/W7125981382","doi":"https://doi.org/10.1109/access.2026.3658360","title":"AURA-Net: A Deep Learning Framework for Robust Authorship Verification in Print-and-Capture Resistant Image Watermarking","display_name":"AURA-Net: A Deep Learning Framework for Robust Authorship Verification in Print-and-Capture Resistant Image Watermarking","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7125981382","doi":"https://doi.org/10.1109/access.2026.3658360"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3658360","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3658360","pdf_url":null,"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://doi.org/10.1109/access.2026.3658360","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124113151","display_name":"Ramyashree","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ramyashree","raw_affiliation_strings":["Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India"],"raw_orcid":"https://orcid.org/0000-0002-0237-2444","affiliations":[{"raw_affiliation_string":"Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124113867","display_name":"P Shashwath","orcid":null},"institutions":[{"id":"https://openalex.org/I1333540553","display_name":"Nitte University","ror":"https://ror.org/029nydt37","country_code":"IN","type":"education","lineage":["https://openalex.org/I1333540553"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"P. Shashwath","raw_affiliation_strings":["Department of Artificial Intelligence and Data Science, NMAM Institute of Technology (NMAMIT), NITTE (Deemed to be University), Karnataka, Nitte, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Data Science, NMAM Institute of Technology (NMAMIT), NITTE (Deemed to be University), Karnataka, Nitte, India","institution_ids":["https://openalex.org/I1333540553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073202319","display_name":"M.S. Muneshwara","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M. S. Muneshwara","raw_affiliation_strings":["BMS Institute of Technology and Management, Bengaluru, Karnataka, India"],"raw_orcid":"https://orcid.org/0000-0003-4714-4100","affiliations":[{"raw_affiliation_string":"BMS Institute of Technology and Management, Bengaluru, Karnataka, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061441269","display_name":"S Raghavendra","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"S. Raghavendra","raw_affiliation_strings":["Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India"],"raw_orcid":"https://orcid.org/0000-0003-2733-3916","affiliations":[{"raw_affiliation_string":"Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124146514","display_name":"B N Anoop","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"B. N. Anoop","raw_affiliation_strings":["Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India"],"raw_orcid":"https://orcid.org/0000-0002-6082-391X","affiliations":[{"raw_affiliation_string":"Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124062911","display_name":"P S Venugopala","orcid":null},"institutions":[{"id":"https://openalex.org/I1333540553","display_name":"Nitte University","ror":"https://ror.org/029nydt37","country_code":"IN","type":"education","lineage":["https://openalex.org/I1333540553"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"P. S. Venugopala","raw_affiliation_strings":["Department of Artificial Intelligence and Data Science, NMAM Institute of Technology (NMAMIT), NITTE (Deemed to be University), Karnataka, Nitte, India"],"raw_orcid":"https://orcid.org/0000-0002-3903-5986","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Data Science, NMAM Institute of Technology (NMAMIT), NITTE (Deemed to be University), Karnataka, Nitte, India","institution_ids":["https://openalex.org/I1333540553"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5124113151"],"corresponding_institution_ids":["https://openalex.org/I164861460"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14915011,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"15506","last_page":"15533"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.8174999952316284,"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":0.8174999952316284,"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":0.1509000062942505,"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/T10828","display_name":"Biometric Identification and Security","score":0.005900000222027302,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/digital-watermarking","display_name":"Digital watermarking","score":0.8313999772071838},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.6811000108718872},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.524399995803833},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.492000013589859},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4578000009059906},{"id":"https://openalex.org/keywords/bitwise-operation","display_name":"Bitwise operation","score":0.44769999384880066},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4352000057697296},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.42879998683929443},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.41269999742507935},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.38749998807907104}],"concepts":[{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.8313999772071838},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8104000091552734},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.6811000108718872},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6406000256538391},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.524399995803833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5152999758720398},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.492000013589859},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4578000009059906},{"id":"https://openalex.org/C134765980","wikidata":"https://www.wikidata.org/wiki/Q879126","display_name":"Bitwise operation","level":2,"score":0.44769999384880066},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4352000057697296},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.42879998683929443},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.41269999742507935},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.38749998807907104},{"id":"https://openalex.org/C2780575108","wikidata":"https://www.wikidata.org/wiki/Q7316652","display_name":"Retargeting","level":2,"score":0.3698999881744385},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.3382999897003174},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.3228999972343445},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C136695289","wikidata":"https://www.wikidata.org/wiki/Q415568","display_name":"Bitstream","level":3,"score":0.31369999051094055},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.29170000553131104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28929999470710754},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2800999879837036},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C177650935","wikidata":"https://www.wikidata.org/wiki/Q1760303","display_name":"Netlist","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C42781572","wikidata":"https://www.wikidata.org/wiki/Q1250322","display_name":"Digital image","level":4,"score":0.27630001306533813},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2678000032901764},{"id":"https://openalex.org/C62725073","wikidata":"https://www.wikidata.org/wiki/Q1771663","display_name":"Image histogram","level":5,"score":0.26019999384880066},{"id":"https://openalex.org/C112416745","wikidata":"https://www.wikidata.org/wiki/Q974213","display_name":"Digital imaging","level":5,"score":0.2587999999523163},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2515000104904175},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3658360","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3658360","pdf_url":null,"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:40c03401fb474c2e987630fe7f8d5dae","is_oa":true,"landing_page_url":"https://doaj.org/article/40c03401fb474c2e987630fe7f8d5dae","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 14, Pp 15506-15533 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3658360","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3658360","pdf_url":null,"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":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4840867817401886}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1600298958","https://openalex.org/W2023802827","https://openalex.org/W2079789955","https://openalex.org/W2081539288","https://openalex.org/W2739757502","https://openalex.org/W2741137940","https://openalex.org/W2895518292","https://openalex.org/W2915130236","https://openalex.org/W3119620012","https://openalex.org/W4205102068","https://openalex.org/W4308146468","https://openalex.org/W4360585604","https://openalex.org/W4383503849","https://openalex.org/W4384304001","https://openalex.org/W4388018933","https://openalex.org/W4399054953","https://openalex.org/W4399729888","https://openalex.org/W4400448067","https://openalex.org/W4400770790","https://openalex.org/W4401567718","https://openalex.org/W4401809180","https://openalex.org/W4403122959","https://openalex.org/W4404371013","https://openalex.org/W4406890112","https://openalex.org/W4409262147","https://openalex.org/W4409513158","https://openalex.org/W4412694115","https://openalex.org/W4413130824"],"related_works":[],"abstract_inverted_index":{"The":[0,74,151],"exponential":[1],"growth":[2],"of":[3,23,61,122,130,188,200,252],"digital":[4,216,284],"imagery":[5],"across":[6,224,282],"online":[7],"and":[8,39,63,87,112,126,145,159,168,196,230,254,262,267,285,291],"printed":[9],"media":[10],"has":[11],"intensified":[12],"the":[13,21,44,84,123,218,275],"need":[14],"for":[15,241,295],"reliable":[16,279],"authorship":[17,297],"verification":[18],"systems.":[19],"Ensuring":[20],"integrity":[22],"embedded":[24,45,85],"watermarks":[25],"becomes":[26],"especially":[27],"challenging":[28],"under":[29,109,148],"print-and-capture":[30],"(P&C)":[31],"conditions,":[32],"where":[33,207],"halftoning,":[34],"optical":[35],"blur,":[36,165,227],"illumination":[37,192],"variation,":[38,167],"sensor":[40],"noise":[41],"jointly":[42,82],"distort":[43],"signal.":[46],"To":[47],"address":[48],"these":[49],"challenges,":[50],"this":[51],"work":[52],"presents":[53],"AURA-Net,":[54],"a":[55,66,77,89,101,119,134,184,198,234,289],"deep":[56],"learning-based":[57],"watermarking":[58],"framework":[59,277],"capable":[60],"embedding":[62,261],"reliably":[64],"recovering":[65],"fixed":[67],"88-bit":[68],"watermark":[69,280],"after":[70],"full":[71],"physical":[72,242,286],"reproduction.":[73],"system":[75],"incorporates":[76],"dual-head":[78],"U-Net":[79],"architecture":[80],"that":[81,181],"predicts":[83],"bitstream":[86],"estimates":[88],"presence":[90,143],"confidence":[91,94,199],"score.":[92],"A":[93],"threshold":[95],"(\u03c4":[96],"=":[97,194,202],"0.76),":[98],"together":[99],"with":[100,249],"bounded":[102],"retry-decoding":[103],"mechanism,":[104],"ensures":[105],"robust":[106],"recovery":[107,208],"even":[108],"difficult":[110],"lighting":[111],"capture":[113],"conditions.":[114],"In":[115],"addition,":[116],"we":[117],"introduce":[118],"mathematical":[120],"formulation":[121],"P&C":[124,136],"process":[125],"an":[127,250],"analytical":[128],"derivation":[129],"AURA-Net\u2019s":[131],"robustness,":[132],"including":[133],"linearized":[135],"degradation":[137],"model,":[138],"latent-space":[139],"margin":[140],"separation,":[141],"likelihood-based":[142],"detection,":[144],"cumulative":[146],"reliability":[147],"retry":[149,212],"decoding.":[150,213],"model":[152,219],"is":[153,209,246],"trained":[154],"using":[155],"progressive":[156],"clean":[157],"masking":[158],"photometric":[160],"distortions":[161],"(JPEG":[162],"compression,":[163,226],"Gaussian":[164],"histogram":[166,257],"synthetic":[169],"noise)":[170],"to":[171,238],"improve":[172],"generalization.":[173],"Experiments":[174],"on":[175],"200":[176],"physically":[177],"captured":[178],"samples":[179],"demonstrate":[180],"AURA-Net":[182,259],"achieves":[183],"mean":[185],"bitwise":[186,222],"accuracy":[187,223],"99.8%":[189],"in":[190,204,264],"good":[191],"(\u03bc":[193],"0.801)":[195],"maintains":[197],"\u03bc":[201],"0.745":[203],"low-light":[205],"settings,":[206],"stabilized":[210],"through":[211],"Under":[214],"purely":[215],"attacks,":[217],"yields":[220],"40.91-44.32%":[221],"JPEG":[225],"salt-and-pepper":[228],"noise,":[229,232],"speckle":[231],"reflecting":[233],"practical":[235],"trade-off":[236],"due":[237],"its":[239],"optimization":[240],"robustness.":[243],"High":[244],"imperceptibility":[245],"consistently":[247],"maintained,":[248],"SSIM":[251],"0.997":[253],"negligible":[255],"grayscale":[256],"deviation.":[258],"executes":[260],"extraction":[263],"0.003":[265],"s":[266],"0.002":[268],"s,":[269],"respectively,":[270],"enabling":[271],"real-time":[272],"deployment.":[273],"Overall,":[274],"proposed":[276],"demonstrates":[278],"preservation":[281],"both":[283],"domains,":[287],"establishing":[288],"reproducible":[290],"analytically":[292],"grounded":[293],"foundation":[294],"post-print":[296],"verification.":[298]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-01-29T00:00:00"}