{"id":"https://openalex.org/W7133352085","doi":"https://doi.org/10.1109/tps-isa67132.2025.00037","title":"Images in Motion?: A First Look Into Video Leakage in Collaborative Deep Learning","display_name":"Images in Motion?: A First Look Into Video Leakage in Collaborative Deep Learning","publication_year":2025,"publication_date":"2025-11-12","ids":{"openalex":"https://openalex.org/W7133352085","doi":"https://doi.org/10.1109/tps-isa67132.2025.00037"},"language":null,"primary_location":{"id":"doi:10.1109/tps-isa67132.2025.00037","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tps-isa67132.2025.00037","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 7th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA)","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/A5033316114","display_name":"Md. Fazle Rasul","orcid":null},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Md Fazle Rasul","raw_affiliation_strings":["Colorado State University,*Department of Computer Science,Fort Collins,CO,80523-1873"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Colorado State University,*Department of Computer Science,Fort Collins,CO,80523-1873","institution_ids":["https://openalex.org/I92446798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119757818","display_name":"Alanood Alqobaisi","orcid":null},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alanood Alqobaisi","raw_affiliation_strings":["Colorado State University,*Department of Computer Science,Fort Collins,CO,80523-1873"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Colorado State University,*Department of Computer Science,Fort Collins,CO,80523-1873","institution_ids":["https://openalex.org/I92446798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026447333","display_name":"Bruhadeshwar Bezawada","orcid":"https://orcid.org/0000-0002-1021-8121"},"institutions":[{"id":"https://openalex.org/I103527128","display_name":"Southern Arkansas University","ror":"https://ror.org/036sak533","country_code":"US","type":"education","lineage":["https://openalex.org/I103527128"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bruhadeshwar Bezawada","raw_affiliation_strings":["Southern Arkansas University,Department of Mathematics and Computer Science,Magnolia,AR,71753-5000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern Arkansas University,Department of Mathematics and Computer Science,Magnolia,AR,71753-5000","institution_ids":["https://openalex.org/I103527128"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5127893254","display_name":"Indrakshi Ray","orcid":null},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Indrakshi Ray","raw_affiliation_strings":["Colorado State University,*Department of Computer Science,Fort Collins,CO,80523-1873"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Colorado State University,*Department of Computer Science,Fort Collins,CO,80523-1873","institution_ids":["https://openalex.org/I92446798"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.66639023,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"282","last_page":"292"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.2304999977350235,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.2304999977350235,"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":0.15649999678134918,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.1396999955177307,"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/classifier","display_name":"Classifier (UML)","score":0.5593000054359436},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5378999710083008},{"id":"https://openalex.org/keywords/leakage","display_name":"Leakage (economics)","score":0.4790000021457672},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.45890000462532043},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4318999946117401},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4009000062942505},{"id":"https://openalex.org/keywords/confidentiality","display_name":"Confidentiality","score":0.39980000257492065},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.3610000014305115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7766000032424927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5652999877929688},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5593000054359436},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5378999710083008},{"id":"https://openalex.org/C2777042071","wikidata":"https://www.wikidata.org/wiki/Q6509304","display_name":"Leakage (economics)","level":2,"score":0.4790000021457672},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.45890000462532043},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4318999946117401},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C71745522","wikidata":"https://www.wikidata.org/wiki/Q2476929","display_name":"Confidentiality","level":2,"score":0.39980000257492065},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3411000072956085},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32679998874664307},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29010000824928284},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C193519340","wikidata":"https://www.wikidata.org/wiki/Q891179","display_name":"Data loss","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tps-isa67132.2025.00037","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tps-isa67132.2025.00037","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 7th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1286238574","display_name":null,"funder_award_id":"CNS 1822118,CNS 2226232,CNS 2335687,DMS 2123761","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2112796928","https://openalex.org/W2133665775","https://openalex.org/W2194775991","https://openalex.org/W2473418344","https://openalex.org/W2526417872","https://openalex.org/W2618530766","https://openalex.org/W2765407302","https://openalex.org/W2781091734","https://openalex.org/W2952524552","https://openalex.org/W2963795951","https://openalex.org/W3035022492","https://openalex.org/W3085804918","https://openalex.org/W3175192640","https://openalex.org/W3204971388","https://openalex.org/W3207743553","https://openalex.org/W4285605911","https://openalex.org/W4382203360","https://openalex.org/W4393148491","https://openalex.org/W4401560516","https://openalex.org/W4402753276","https://openalex.org/W4406880870","https://openalex.org/W4409364270"],"related_works":[],"abstract_inverted_index":{"Federated":[0],"learning":[1],"(FL)":[2],"allows":[3],"multiple":[4],"entities":[5],"to":[6,173,188],"train":[7],"a":[8,229],"shared":[9,68],"model":[10,21],"collaboratively.":[11],"Its":[12],"core,":[13],"privacy-preserving":[14],"principle":[15],"is":[16,34,53,81,210,228],"that":[17,130,142,158,201,222],"participants":[18],"only":[19],"exchange":[20],"updates,":[22],"such":[23],"as":[24],"gradients,":[25,69],"and":[26,42,86,128,232],"never":[27],"their":[28,89],"raw,":[29],"sensitive":[30],"data.":[31],"This":[32,100],"approach":[33],"fundamental":[35],"for":[36,83],"applications":[37],"in":[38,110,226],"domains":[39],"where":[40,183],"privacy":[41],"confidentiality":[43],"are":[44],"important.":[45],"However,":[46],"the":[47,67,71,76,103,143,164,184,196,214,233],"security":[48],"of":[49,73,78,98,106,145],"this":[50,180],"very":[51],"mechanism":[52],"threatened":[54],"by":[55],"gradient":[56,113,152,168],"inversion":[57,114,153,169],"attacks,":[58,170],"which":[59,236],"can":[60,162],"reverse-engineer":[61],"private":[62],"training":[63],"data":[64,93,108,224],"directly":[65],"from":[66,195],"defeating":[70],"purpose":[72],"FL.":[74],"While":[75],"impact":[77],"these":[79],"attacks":[80,206],"known":[82],"image,":[84],"text,":[85],"tabular":[87],"data,":[88],"effect":[90],"on":[91],"video":[92,107,120,133,223],"remains":[94],"an":[95],"unexamined":[96],"area":[97],"research.":[99],"paper":[101],"presents":[102],"first":[104],"analysis":[105],"leakage":[109,209,225],"FL":[111,227],"using":[112],"attacks.":[115,154],"We":[116,155,199],"evaluate":[117],"two":[118],"common":[119],"classification":[121],"approaches:":[122],"one":[123],"employing":[124],"pretrained":[125],"feature":[126,146,203],"extractors":[127,147,204],"another":[129],"processes":[131],"raw":[132],"frames":[134,165,194],"with":[135],"simple":[136],"transformations.":[137],"Our":[138,177],"initial":[139],"results":[140],"indicate":[141],"use":[144],"offers":[148],"greater":[149],"resilience":[150],"against":[151],"also":[156],"demonstrate":[157],"image":[159],"super-resolution":[160],"techniques":[161],"enhance":[163],"extracted":[166],"through":[167],"enabling":[171],"attackers":[172],"reconstruct":[174],"higher-quality":[175],"videos.":[176],"experiments":[178],"validate":[179],"across":[181],"scenarios":[182],"attacker":[185],"has":[186],"access":[187],"zero,":[189],"one,":[190],"or":[191],"more":[192,207],"reference":[193],"target":[197],"environment.":[198],"find":[200],"although":[202],"make":[205],"challenging,":[208],"still":[211],"possible":[212],"if":[213],"classifier":[215],"lacks":[216],"sufficient":[217],"complexity.":[218],"We,":[219],"therefore,":[220],"conclude":[221],"viable":[230],"threat,":[231],"conditions":[234],"under":[235],"it":[237],"occurs":[238],"warrant":[239],"further":[240],"investigation.":[241]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-04T00:00:00"}
