{"id":"https://openalex.org/W7159639690","doi":"https://doi.org/10.48550/arxiv.2604.27002","title":"Membership Inference Attacks Against Video Large Language Models","display_name":"Membership Inference Attacks Against Video Large Language Models","publication_year":2026,"publication_date":"2026-04-29","ids":{"openalex":"https://openalex.org/W7159639690","doi":"https://doi.org/10.48550/arxiv.2604.27002"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.27002","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27002","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2604.27002","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134992650","display_name":"Wei Song","orcid":"https://orcid.org/0000-0001-6240-5706"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134972467","display_name":"Yuxin Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Yuxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134973431","display_name":"Ziqi Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Ziqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134986082","display_name":"Yi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134966520","display_name":"Gelei Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Gelei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134973106","display_name":"Yuekang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yuekang","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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.7070000171661377,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.7070000171661377,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.05590000003576279,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.03700000047683716,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/inference","display_name":"Inference","score":0.7120000123977661},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.45820000767707825},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.45649999380111694},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.45489999651908875},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.41690000891685486},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.41620001196861267},{"id":"https://openalex.org/keywords/audit","display_name":"Audit","score":0.3776000142097473}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7498999834060669},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7120000123977661},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5371999740600586},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.45820000767707825},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.45649999380111694},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.45489999651908875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41819998621940613},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41620001196861267},{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.3776000142097473},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36970001459121704},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.35740000009536743},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3221000134944916},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3125},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.28200000524520874},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.28200000524520874},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C61123122","wikidata":"https://www.wikidata.org/wiki/Q281287","display_name":"Politeness","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.26910001039505005},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.27002","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27002","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.27002","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27002","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6581491231918335}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video":[0],"large":[1],"language":[2],"models":[3],"(VideoLLMs)":[4],"are":[5,182],"increasingly":[6],"trained":[7],"or":[8],"instruction-tuned":[9],"on":[10],"large-scale":[11],"video--text":[12],"corpora":[13],"collected":[14],"from":[15],"heterogeneous":[16],"sources,":[17],"raising":[18],"an":[19,24,190],"immediate":[20],"privacy":[21,201],"question:":[22],"can":[23],"external":[25],"auditor":[26],"determine":[27],"whether":[28],"a":[29,93,167],"particular":[30],"video":[31],"was":[32],"used":[33],"during":[34],"training?":[35],"While":[36],"membership":[37,74,186],"inference":[38,169,187],"attacks":[39],"(MIAs)":[40],"have":[41],"been":[42],"studied":[43],"extensively":[44],"for":[45,50,193],"classifiers":[46],"and,":[47],"more":[48,117],"recently,":[49],"text":[51],"and":[52,85,124,148,165,173,199],"image":[53],"generation":[54,101,119],"models,":[55],"the":[56,73,133,137,143,152,156,161,194],"VideoLLM":[57],"setting":[58,62],"remains":[59],"unexplored.":[60],"This":[61],"is":[63,76,109],"challenging":[64],"because":[65],"black-box":[66,94,185],"auditors":[67],"observe":[68],"only":[69],"generated":[70],"text,":[71],"whereas":[72],"signal":[75,127],"entangled":[77],"with":[78,102,132],"video-specific":[79],"factors":[80],"such":[81],"as":[82],"motion":[83],"complexity":[84],"temporal":[86],"span.":[87],"In":[88],"this":[89,126],"paper,":[90],"we":[91,141],"present":[92],"MIA":[95],"targeting":[96],"VideoLLMs":[97],"that":[98,110,125,180],"couples":[99],"temperature-perturbed":[100],"video-aware":[103],"difficulty":[104,135],"features.":[105],"Our":[106],"key":[107],"intuition":[108],"member":[111,168],"samples":[112],"tend":[113],"to":[114,184,196],"induce":[115],"sharper,":[116],"brittle":[118],"behavior":[120],"across":[121],"decoding":[122],"temperatures,":[123,150],"should":[128],"be":[129],"interpreted":[130],"jointly":[131],"intrinsic":[134],"of":[136,171,175],"queried":[138],"video.":[139],"Concretely,":[140],"query":[142],"target":[144],"model":[145],"at":[146],"low":[147],"high":[149],"measure":[151],"semantic":[153],"drift":[154],"between":[155],"resulting":[157],"texts.":[158],"We":[159],"evaluate":[160,198],"attack":[162],"against":[163],"\\texttt{LLaVA-Video-7B-Qwen2-Video-Only}":[164],"achieve":[166],"AUC":[170],"0.68":[172],"accuracy":[174],"0.63.":[176],"These":[177],"results":[178],"demonstrate":[179],"Video-LLMs":[181],"vulnerable":[183],"attacks,":[188],"highlighting":[189],"urgent":[191],"need":[192],"community":[195],"systematically":[197],"mitigate":[200],"risks":[202],"in":[203],"VideoLLMs.":[204]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-02T00:00:00"}