{"id":"https://openalex.org/W7166835056","doi":"https://doi.org/10.48550/arxiv.2606.31427","title":"No Prompt, No Leaks: A Robust Generative Steganography Framework via Prompt-Free Diffusion","display_name":"No Prompt, No Leaks: A Robust Generative Steganography Framework via Prompt-Free Diffusion","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7166835056","doi":"https://doi.org/10.48550/arxiv.2606.31427"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.31427","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31427","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.31427","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112212946","display_name":"Jingwen Cai","orcid":"https://orcid.org/0009-0004-0580-6270"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Jingwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035423120","display_name":"Fen Xiao","orcid":"https://orcid.org/0000-0001-7511-9418"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Fen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130933215","display_name":"Shuhua Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Shuhua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5103668258","display_name":"Gao X","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Xieping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.7876999974250793,"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":0.7876999974250793,"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":0.15520000457763672,"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":0.011900000274181366,"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":0.7918000221252441},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5515000224113464},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5097000002861023},{"id":"https://openalex.org/keywords/steganalysis","display_name":"Steganalysis","score":0.492000013589859},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.43880000710487366},{"id":"https://openalex.org/keywords/information-hiding","display_name":"Information hiding","score":0.42809998989105225},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3968000113964081},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.39500001072883606}],"concepts":[{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.7918000221252441},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6355000138282776},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5630999803543091},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5515000224113464},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5097000002861023},{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.492000013589859},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.43880000710487366},{"id":"https://openalex.org/C3073032","wikidata":"https://www.wikidata.org/wiki/Q15912075","display_name":"Information hiding","level":3,"score":0.42809998989105225},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39719998836517334},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3968000113964081},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.39500001072883606},{"id":"https://openalex.org/C50637493","wikidata":"https://www.wikidata.org/wiki/Q1136781","display_name":"Morphing","level":2,"score":0.3711000084877014},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.365200012922287},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.34119999408721924},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.32600000500679016},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2930000126361847},{"id":"https://openalex.org/C13179402","wikidata":"https://www.wikidata.org/wiki/Q7606662","display_name":"Steganography tools","level":4,"score":0.2854999899864197},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.31427","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31427","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.31427","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31427","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generative":[0],"image":[1,25,65,80,97,174],"steganography":[2,26,66],"synthesizes":[3],"stego":[4,50,79,122],"images":[5,51],"directly":[6],"from":[7,129,147],"secret":[8,30,55,96,173],"information":[9],"to":[10,47,73,111,139,166],"achieve":[11],"inherent":[12],"security":[13],"advantages.":[14],"Latent":[15],"Diffusion":[16],"Models":[17],"(LDMs)":[18],"have":[19],"recently":[20],"emerged":[21],"as":[22],"a":[23,62,83,90,95,134],"fundamental":[24],"framework":[27,67],"that":[28,68,158],"modulates":[29],"latent":[31,100,113],"representations":[32],"with":[33],"text":[34,41],"prompts.":[35],"Limited":[36],"by":[37],"the":[38,108,120,130,142,148,159],"inflexibility":[39],"of":[40,171],"prompts,":[42],"these":[43],"methods":[44,168],"still":[45],"struggle":[46],"generate":[48],"high-quality":[49],"and":[52,77,98,115,150,177],"accurately":[53],"recover":[54],"images.":[56,123],"In":[57],"this":[58],"work,":[59],"we":[60],"propose":[61],"prompt-free":[63],"diffusion":[64,109],"integrates":[69],"style":[70,103],"semantic":[71],"priors":[72],"control":[74,112],"more":[75],"robust":[76],"reliable":[78],"generation.":[81],"Specifically,":[82],"Cascaded":[84],"Affine":[85],"Coupling":[86],"Module":[87],"(CACM)":[88],"establishes":[89],"bijective,":[91],"deterministic":[92],"mapping":[93],"between":[94],"its":[99],"representation.":[101],"Then,":[102],"semantics":[104],"are":[105],"integrated":[106],"into":[107],"process":[110],"representation":[114],"ensure":[116],"visual":[117],"imperceptibility":[118],"in":[119,169],"generated":[121],"To":[124],"mitigate":[125],"trajectory":[126,144],"deviations":[127],"stemming":[128],"unconditioned":[131],"reverse":[132],"process,":[133],"predictor-corrector":[135],"mechanism":[136],"is":[137],"introduced":[138],"iteratively":[140],"refine":[141],"generation":[143],"via":[145],"feedback":[146],"current":[149],"predicted":[151],"next":[152],"states.":[153],"Extensive":[154],"experimental":[155],"results":[156],"show":[157],"proposed":[160],"method":[161],"achieves":[162],"competitive":[163],"performance":[164],"compared":[165],"state-of-the-art":[167],"terms":[170],"security,":[172],"reconstruction":[175],"accuracy":[176],"controllability.":[178]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-02T00:00:00"}
