{"id":"https://openalex.org/W2809603988","doi":"https://doi.org/10.1145/3206004.3206024","title":"Deep Learning in Multimedia Forensics","display_name":"Deep Learning in Multimedia Forensics","publication_year":2018,"publication_date":"2018-06-14","ids":{"openalex":"https://openalex.org/W2809603988","doi":"https://doi.org/10.1145/3206004.3206024","mag":"2809603988"},"language":"en","primary_location":{"id":"doi:10.1145/3206004.3206024","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3206004.3206024","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3206004.3206024","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM Workshop on Information Hiding and Multimedia Security","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3206004.3206024","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080842029","display_name":"Luisa Verdoliva","orcid":"https://orcid.org/0000-0001-7286-7963"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Luisa Verdoliva","raw_affiliation_strings":["University Federico II of Naples, Naples, Italy"],"affiliations":[{"raw_affiliation_string":"University Federico II of Naples, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5080842029"],"corresponding_institution_ids":["https://openalex.org/I71267560"],"apc_list":null,"apc_paid":null,"fwci":0.1045,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.42918455,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3","last_page":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9998999834060669,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9965000152587891,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9955000281333923,"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/computer-science","display_name":"Computer science","score":0.8211207389831543},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7327454090118408},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7013733983039856},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6755800247192383},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5744306445121765},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5424301624298096},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.48241767287254333},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3659387230873108}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8211207389831543},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7327454090118408},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7013733983039856},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6755800247192383},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5744306445121765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5424301624298096},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.48241767287254333},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3659387230873108},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3206004.3206024","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3206004.3206024","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3206004.3206024","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM Workshop on Information Hiding and Multimedia Security","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3206004.3206024","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3206004.3206024","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3206004.3206024","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM Workshop on Information Hiding and Multimedia Security","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G4265454910","display_name":null,"funder_award_id":"FA8750-16-2-0204","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2809603988.pdf","grobid_xml":"https://content.openalex.org/works/W2809603988.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"With":[0],"the":[1,19,45,52,79,92,95,118,125,166,171,177,213],"widespread":[2],"diffusion":[3],"of":[4,38,65,86,94,212,215],"powerful":[5,129],"media":[6,175],"editing":[7],"tools,":[8],"falsifying":[9],"images":[10,199],"and":[11,16,44,75,152,159,200],"videos":[12,201],"has":[13,56],"become":[14],"easier":[15,17],"in":[18,35,41,170],"last":[20],"few":[21],"years.":[22],"Fake":[23],"multimedia,":[24],"often":[25],"used":[26],"to":[27,49,110,149,157,173,192],"support":[28],"fake":[29],"news,":[30],"represents":[31],"a":[32,58,133,143,153],"growing":[33],"menace":[34],"many":[36],"fields":[37],"life,":[39],"notably":[40],"politics,":[42],"journalism,":[43],"judiciary.":[46],"In":[47,161,208],"response":[48],"this":[50,162],"threat,":[51],"signal":[53,81],"processing":[54,82],"community":[55],"produced":[57],"major":[59],"research":[60],"effort.":[61],"A":[62],"large":[63,135],"number":[64],"methods":[66,102,220],"have":[67,107],"been":[68,108],"proposed":[69,109,169],"for":[70],"source":[71],"identification,":[72],"forgery":[73],"detection":[74],"localization,":[76],"relying":[77,181],"on":[78,104,182,218],"typical":[80],"tools.":[83,131],"The":[84],"advent":[85],"deep":[87,105,121,138],"learning,":[88],"however,":[89],"is":[90],"changing":[91],"rules":[93],"game.":[96],"On":[97,117],"one":[98],"hand,":[99,120],"new":[100,128],"sophisticated":[101],"based":[103],"learning":[106,122,139],"accomplish":[111],"manipulations":[112],"that":[113],"were":[114],"previously":[115],"unthinkable.":[116],"other":[119],"provides":[123],"also":[124],"analyst":[126],"with":[127,147,189],"forensic":[130],"Given":[132],"suitably":[134],"training":[136],"set,":[137],"architectures":[140],"ensure":[141,174],"usually":[142],"significant":[144],"performance":[145],"gain":[146],"respect":[148],"conventional":[150],"methods,":[151],"much":[154],"higher":[155],"robustness":[156],"post-processing":[158],"evasions.":[160],"talk":[163],"after":[164],"reviewing":[165],"main":[167],"approaches":[168],"literature":[172],"authenticity,":[176],"most":[178],"promising":[179],"solutions":[180],"Convolutional":[183],"Neural":[184],"Networks":[185],"will":[186,221],"be":[187,222],"explored":[188],"special":[190],"attention":[191],"realistic":[193],"scenarios,":[194],"such":[195,219],"as":[196],"when":[197],"manipulated":[198],"are":[202],"spread":[203],"out":[204],"over":[205],"social":[206],"networks.":[207],"addition,":[209],"an":[210],"analysis":[211],"efficacy":[214],"adversarial":[216],"attacks":[217],"presented.":[223]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}