{"id":"https://openalex.org/W7156809417","doi":"https://doi.org/10.48550/arxiv.2604.23957","title":"LAVA: Layered Audio-Visual Anti-tampering Watermarking for Robust Deepfake Detection and Localization","display_name":"LAVA: Layered Audio-Visual Anti-tampering Watermarking for Robust Deepfake Detection and Localization","publication_year":2026,"publication_date":"2026-04-27","ids":{"openalex":"https://openalex.org/W7156809417","doi":"https://doi.org/10.48550/arxiv.2604.23957"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.23957","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23957","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2604.23957","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134774610","display_name":"Bokang Zeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Bokang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134821064","display_name":"Zheng Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134775920","display_name":"Xiaoyu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xiaoyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134792927","display_name":"Xiaoyan Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Xiaoyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134793940","display_name":"Jiaojiao Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Jiaojiao","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":0.5174999833106995,"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":0.5174999833106995,"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":0.41260001063346863,"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.017799999564886093,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.9064000248908997},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.7835000157356262},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.47609999775886536},{"id":"https://openalex.org/keywords/codec","display_name":"Codec","score":0.47040000557899475},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.46650001406669617},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4438999891281128},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.39100000262260437},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.38530001044273376}],"concepts":[{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.9064000248908997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7942000031471252},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.7835000157356262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6718999743461609},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5613999962806702},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.47609999775886536},{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.47040000557899475},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.46650001406669617},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4438999891281128},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.39100000262260437},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.38530001044273376},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3562000095844269},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.2939000129699707},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2727999985218048}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.23957","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23957","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2604.23957","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23957","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[{"score":0.517116129398346,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Proactive":[0],"watermarking":[1,48],"offers":[2],"a":[3,76],"promising":[4],"approach":[5],"for":[6,82],"deepfake":[7,83],"tamper":[8,35,84,101,110,134],"detection":[9,85,119],"and":[10,21,24,41,86,93,99,105,128,131],"localization":[11,36,135],"in":[12],"short-form":[13],"videos.":[14],"However,":[15],"existing":[16,45,138],"methods":[17,49],"often":[18,50],"decouple":[19],"audio":[20],"visual":[22,47],"evidence":[23,102],"assume":[25],"that":[26,115],"watermark":[27,79,91],"signals":[28],"remain":[29],"reliable":[30,100],"under":[31,53,103],"real-world":[32],"degradations,":[33],"making":[34],"vulnerable":[37],"to":[38,96,126],"multimodal":[39,129],"misalignment":[40],"compression":[42,55,104,127],"distortions.":[43],"Moreover,":[44],"semi-fragile":[46],"degrade":[51],"significantly":[52,132],"codec":[54],"because":[56],"their":[57],"embedding":[58],"bands":[59],"overlap":[60],"with":[61],"compression-sensitive":[62],"frequency":[63],"regions.":[64],"To":[65],"address":[66],"these":[67],"limitations,":[68],"we":[69],"propose":[70],"Layered":[71],"Audio-Visual":[72],"Anti-tampering":[73],"Watermarking":[74],"(LAVA),":[75],"calibration-aware":[77,94],"audio-visual":[78,106,139],"fusion":[80,92,140],"framework":[81],"localization.":[87,111],"LAVA":[88,116],"leverages":[89],"cross-modal":[90],"alignment":[95],"preserve":[97],"consistent":[98],"asynchrony,":[107],"enabling":[108],"robust":[109,125],"Extensive":[112],"experiments":[113],"demonstrate":[114],"achieves":[117],"near-perfect":[118],"performance":[120],"(AP":[121],"=":[122],"0.999),":[123],"remains":[124],"misalignment,":[130],"improves":[133],"reliability":[136],"over":[137],"baselines.":[141]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-29T00:00:00"}