{"id":"https://openalex.org/W7127564757","doi":"https://doi.org/10.1109/ccnc65079.2026.11366470","title":"Provenance of AI-Generated Images: A Vector Similarity and Blockchain-based Approach","display_name":"Provenance of AI-Generated Images: A Vector Similarity and Blockchain-based Approach","publication_year":2026,"publication_date":"2026-01-09","ids":{"openalex":"https://openalex.org/W7127564757","doi":"https://doi.org/10.1109/ccnc65079.2026.11366470"},"language":null,"primary_location":{"id":"doi:10.1109/ccnc65079.2026.11366470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc65079.2026.11366470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 23rd Consumer Communications &amp;amp; Networking Conference (CCNC)","raw_type":"proceedings-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/A5109971914","display_name":"Jitendra Sharma","orcid":null},"institutions":[{"id":"https://openalex.org/I83328450","display_name":"Miami University","ror":"https://ror.org/05nbqxr67","country_code":"US","type":"education","lineage":["https://openalex.org/I83328450"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jitendra Sharma","raw_affiliation_strings":["Miami University,Department of Computer Science and Software Engineering,Oxford,Ohio"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Miami University,Department of Computer Science and Software Engineering,Oxford,Ohio","institution_ids":["https://openalex.org/I83328450"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103842792","display_name":"Arthur Carvalho","orcid":null},"institutions":[{"id":"https://openalex.org/I83328450","display_name":"Miami University","ror":"https://ror.org/05nbqxr67","country_code":"US","type":"education","lineage":["https://openalex.org/I83328450"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arthur Carvalho","raw_affiliation_strings":["Miami University,Farmer School of Business,Oxford,Ohio"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Miami University,Farmer School of Business,Oxford,Ohio","institution_ids":["https://openalex.org/I83328450"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041907021","display_name":"Suman Bhunia","orcid":"https://orcid.org/0000-0003-3587-3509"},"institutions":[{"id":"https://openalex.org/I83328450","display_name":"Miami University","ror":"https://ror.org/05nbqxr67","country_code":"US","type":"education","lineage":["https://openalex.org/I83328450"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suman Bhunia","raw_affiliation_strings":["Miami University,Department of Computer Science and Software Engineering,Oxford,Ohio"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Miami University,Department of Computer Science and Software Engineering,Oxford,Ohio","institution_ids":["https://openalex.org/I83328450"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5109971914"],"corresponding_institution_ids":["https://openalex.org/I83328450"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20125342,"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":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.14149999618530273,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.14149999618530273,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.07100000232458115,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.06710000336170197,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6796000003814697},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6581000089645386},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5766000151634216},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5033000111579895},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.436599999666214},{"id":"https://openalex.org/keywords/digital-image","display_name":"Digital image","score":0.4065000116825104},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3659000098705292}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6796000003814697},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6581000089645386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6209999918937683},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6086000204086304},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5766000151634216},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5033000111579895},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.436599999666214},{"id":"https://openalex.org/C42781572","wikidata":"https://www.wikidata.org/wiki/Q1250322","display_name":"Digital image","level":4,"score":0.4065000116825104},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3659000098705292},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.34540000557899475},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3443000018596649},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3124000132083893},{"id":"https://openalex.org/C2989087649","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Image synthesis","level":3,"score":0.30230000615119934},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C2779597229","wikidata":"https://www.wikidata.org/wiki/Q17146505","display_name":"Similarity learning","level":3,"score":0.26440000534057617},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.262800008058548},{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccnc65079.2026.11366470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc65079.2026.11366470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 23rd Consumer Communications &amp;amp; Networking Conference (CCNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1964981411","https://openalex.org/W4375869427","https://openalex.org/W4386071953","https://openalex.org/W4387140156","https://openalex.org/W4388495872","https://openalex.org/W4388858443","https://openalex.org/W4389742134","https://openalex.org/W4396685186"],"related_works":[],"abstract_inverted_index":{"Rapid":[0],"advancement":[1],"in":[2,71],"generative":[3],"AI":[4],"and":[5,17,29,52,57,68,131],"large":[6],"language":[7],"models":[8,31],"(LLMs)":[9],"has":[10],"enabled":[11],"the":[12,55,94,158,163,166,176],"creation":[13],"of":[14,59,129,165],"highly":[15],"realistic":[16],"context-aware":[18],"digital":[19,60,72],"content.":[20],"Multimodal":[21],"systems":[22],"such":[23,146],"as":[24,147],"ChatGPT":[25],"with":[26,144,179],"DALL-E":[27],"integration":[28],"diffusion":[30],"like":[32],"Stable":[33],"Diffusion":[34],"can":[35],"now":[36],"generate":[37],"images":[38,83,98,109,133,155,181],"that":[39,96,124,169],"are":[40],"often":[41],"indistinguishable":[42],"from":[43],"human-created":[44,108],"media,":[45],"posing":[46],"significant":[47],"challenges":[48],"for":[49,64,80],"content":[50],"authenticity":[51],"provenance.":[53],"Ensuring":[54],"integrity":[56],"origin":[58],"data":[61],"is":[62,91],"critical":[63],"preserving":[65],"trust,":[66],"accountability,":[67],"legal":[69],"compliance":[70],"ecosystems.":[73],"This":[74],"paper":[75],"presents":[76],"an":[77],"embedding-based":[78],"framework":[79],"detecting":[81],"AI-generated":[82,97,154],"using":[84,134],"vector":[85],"similarity":[86,184],"analysis.":[87],"The":[88],"proposed":[89],"approach":[90],"based":[92],"on":[93,175],"hypothesis":[95,118],"exhibit":[99],"closer":[100],"embedding":[101,137,177],"proximity":[102],"to":[103,156,185],"other":[104],"synthetic":[105],"content,":[106],"whereas":[107],"cluster":[110],"within":[111],"distinct":[112],"semantic":[113],"regions.":[114],"We":[115],"validate":[116],"this":[117],"by":[119],"developing":[120],"a":[121,126],"prototype":[122],"system":[123],"processes":[125],"diverse":[127],"dataset":[128],"AI-":[130],"human-generated":[132],"five":[135],"benchmark":[136],"models.":[138],"Furthermore":[139],"we":[140],"investigated":[141],"whether":[142],"perturbation":[143],"image,":[145],"blurring":[148],"or":[149],"putting":[150],"patches,":[151],"would":[152],"allow":[153],"confuse":[157],"system.":[159],"Experimental":[160],"results":[161],"confirm":[162],"robustness":[164],"method,":[167],"showing":[168],"image":[170],"perturbations":[171],"have":[172],"minimal":[173],"impact":[174],"space,":[178],"altered":[180],"retaining":[182],"high":[183],"their":[186],"originals.":[187]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-02-06T00:00:00"}
