{"id":"https://openalex.org/W7093336944","doi":"https://doi.org/10.1109/lsp.2025.3624083","title":"Denoising Diffusion Probabilistic Steganography Based on Standardized Secret Noise","display_name":"Denoising Diffusion Probabilistic Steganography Based on Standardized Secret Noise","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7093336944","doi":"https://doi.org/10.1109/lsp.2025.3624083"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2025.3624083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3624083","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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":null,"display_name":"Xiang Zhang","orcid":"https://orcid.org/0000-0002-0827-9443"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Zhang","raw_affiliation_strings":["Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-0827-9443","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tianheng Song","orcid":"https://orcid.org/0009-0009-1546-2244"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianheng Song","raw_affiliation_strings":["Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0009-1546-2244","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Fei Peng","orcid":"https://orcid.org/0000-0001-8053-4587"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Peng","raw_affiliation_strings":["School of Artificial Intelligence, Guangzhou University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-8053-4587","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ziwen He","orcid":"https://orcid.org/0000-0002-1019-3884"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziwen He","raw_affiliation_strings":["Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-1019-3884","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Daoyong Fu","orcid":"https://orcid.org/0000-0002-6874-2436"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daoyong Fu","raw_affiliation_strings":["Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-6874-2436","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bei Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132195","display_name":"Guangdong Province Environmental Monitoring Center","ror":"https://ror.org/03gfeke93","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132195"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bei Yuan","raw_affiliation_strings":["Shenzhen Futian Basic Education Quality Monitoring Center, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Futian Basic Education Quality Monitoring Center, Guangzhou, China","institution_ids":["https://openalex.org/I4210132195"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhangjie Fu","orcid":"https://orcid.org/0000-0002-4363-2521"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangjie Fu","raw_affiliation_strings":["Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-4363-2521","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.47783522,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":null,"first_page":"4124","last_page":"4128"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9154000282287598,"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":0.9154000282287598,"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/T11017","display_name":"Chaos-based Image/Signal Encryption","score":0.02329999953508377,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.017799999564886093,"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/steganography","display_name":"Steganography","score":0.7444999814033508},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5782999992370605},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5242999792098999},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48100000619888306},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.46389999985694885},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.44920000433921814},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.44749999046325684},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4424999952316284},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43160000443458557},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.34950000047683716}],"concepts":[{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.7444999814033508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6190000176429749},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5782999992370605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5404000282287598},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5242999792098999},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48100000619888306},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.46389999985694885},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45969998836517334},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.44920000433921814},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4424999952316284},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43160000443458557},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.34950000047683716},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.34689998626708984},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3190000057220459},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.31839999556541443},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2985000014305115},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.2921000123023987},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C3073032","wikidata":"https://www.wikidata.org/wiki/Q15912075","display_name":"Information hiding","level":3,"score":0.28189998865127563},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2815000116825104},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2694000005722046},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.2669000029563904},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2025.3624083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3624083","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G331018939","display_name":null,"funder_award_id":"U22B2062","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3998872663","display_name":null,"funder_award_id":"62372128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4712940882","display_name":null,"funder_award_id":"62401270","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5475295693","display_name":null,"funder_award_id":"2023M741778","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G7931053589","display_name":null,"funder_award_id":"62202234","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8642413541","display_name":null,"funder_award_id":"2023A1515011575","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G975555798","display_name":null,"funder_award_id":"62172232","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"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W68733909","https://openalex.org/W1861492603","https://openalex.org/W2092264651","https://openalex.org/W2322622188","https://openalex.org/W2621048556","https://openalex.org/W2892948265","https://openalex.org/W2969585684","https://openalex.org/W3046549894","https://openalex.org/W3214742360","https://openalex.org/W4312540108","https://openalex.org/W4312933868","https://openalex.org/W4366492959","https://openalex.org/W4387969350","https://openalex.org/W4388283577","https://openalex.org/W4392693721","https://openalex.org/W4395056684","https://openalex.org/W4401386747","https://openalex.org/W4401608840","https://openalex.org/W4402039692","https://openalex.org/W4403792222","https://openalex.org/W4407247376","https://openalex.org/W4410857835"],"related_works":[],"abstract_inverted_index":{"Generative":[0],"steganography":[1],"based":[2],"on":[3],"diffusion":[4,20,110,127],"model":[5,111],"is":[6],"a":[7,16,32,77,134],"technique":[8,39],"that":[9],"directly":[10],"uses":[11],"secret":[12],"information":[13],"to":[14,23,27,63,138],"generate":[15],"stego":[17,55,91,144],"image":[18,46,149],"by":[19],"model.":[21],"Due":[22],"its":[24],"strong":[25],"resistance":[26],"steganalysis,":[28],"it":[29],"has":[30],"become":[31],"hotspot":[33],"in":[34,108],"current":[35],"research.":[36],"However,":[37],"this":[38],"faces":[40],"the":[41,51,54,71,85,90,94,101,104,109,120,125,141,159],"core":[42],"issue":[43],"of":[44,89,103,124,143],"insufficient":[45],"quality,":[47],"which":[48],"stems":[49],"from":[50,70],"mismatch":[52],"between":[53],"noise":[56,65,82,92],"distribution":[57],"and":[58,68,87,112,133,167],"standard":[59,95],"Gaussian":[60,96],"distribution,":[61,83],"leading":[62],"cumulative":[64],"prediction":[66],"errors":[67],"deviation":[69],"generation":[72,142],"path.":[73],"This":[74,98],"paper":[75],"designs":[76],"precise":[78],"alignment":[79],"strategy":[80],"for":[81],"matching":[84],"mean":[86],"covariance":[88],"with":[93,130,156],"distribution.":[97],"theoretically":[99],"ensures":[100],"optimality":[102],"reverse":[105],"denoising":[106],"path":[107],"significantly":[113,162],"reduces":[114],"error":[115],"accumulation.":[116],"Furthermore,":[117],"we":[118],"leverage":[119],"text":[121],"control":[122],"capability":[123],"pre-trained":[126],"model,":[128],"combined":[129],"semantic":[131],"vectors":[132],"cross":[135],"attention":[136],"mechanism,":[137],"dynamically":[139],"adjust":[140],"content,":[145],"achieving":[146],"high":[147],"quality":[148,166],"synthesis.":[150],"Experimental":[151],"results":[152],"show":[153],"that,":[154],"compared":[155],"existing":[157],"methods,":[158],"proposed":[160],"approach":[161],"improves":[163],"both":[164],"visual":[165],"robustness.":[168]},"counts_by_year":[],"updated_date":"2025-11-06T23:17:08.748858","created_date":"2025-10-24T00:00:00"}
