{"id":"https://openalex.org/W3012229420","doi":"https://doi.org/10.1109/wifs47025.2019.9035110","title":"Adversarial CNN Training Under JPEG Laundering Attacks: a Game-Theoretic Approach","display_name":"Adversarial CNN Training Under JPEG Laundering Attacks: a Game-Theoretic Approach","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3012229420","doi":"https://doi.org/10.1109/wifs47025.2019.9035110","mag":"3012229420"},"language":"en","primary_location":{"id":"doi:10.1109/wifs47025.2019.9035110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wifs47025.2019.9035110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Workshop on Information Forensics and Security (WIFS)","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/A5007836692","display_name":"Mauro Barni","orcid":"https://orcid.org/0000-0002-7368-0866"},"institutions":[{"id":"https://openalex.org/I102064193","display_name":"University of Siena","ror":"https://ror.org/01tevnk56","country_code":"IT","type":"education","lineage":["https://openalex.org/I102064193"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Mauro Barni","raw_affiliation_strings":["Department of Information Engineering and Mathematics, University of Siena, Siena, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Mathematics, University of Siena, Siena, Italy","institution_ids":["https://openalex.org/I102064193"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029061070","display_name":"Dequ Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dequ Huang","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing and Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing and Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365163","display_name":"Bin Li","orcid":"https://orcid.org/0000-0002-2613-5451"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Li","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing and Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing and Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026139768","display_name":"Benedetta Tondi","orcid":"https://orcid.org/0000-0002-7518-046X"},"institutions":[{"id":"https://openalex.org/I102064193","display_name":"University of Siena","ror":"https://ror.org/01tevnk56","country_code":"IT","type":"education","lineage":["https://openalex.org/I102064193"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Benedetta Tondi","raw_affiliation_strings":["Department of Information Engineering and Mathematics, University of Siena, Siena, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Mathematics, University of Siena, Siena, Italy","institution_ids":["https://openalex.org/I102064193"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5007836692"],"corresponding_institution_ids":["https://openalex.org/I102064193"],"apc_list":null,"apc_paid":null,"fwci":0.1022,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.48988633,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2019","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":1.0,"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":1.0,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9911999702453613,"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":0.9704999923706055,"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":0.8086850047111511},{"id":"https://openalex.org/keywords/jpeg","display_name":"JPEG","score":0.7779132127761841},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6106695532798767},{"id":"https://openalex.org/keywords/lossless-jpeg","display_name":"Lossless JPEG","score":0.5881863832473755},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5396584868431091},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4420171082019806},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35561686754226685},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2936621904373169},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.26341432332992554},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.23612725734710693}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8086850047111511},{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.7779132127761841},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6106695532798767},{"id":"https://openalex.org/C8384606","wikidata":"https://www.wikidata.org/wiki/Q2190356","display_name":"Lossless JPEG","level":5,"score":0.5881863832473755},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5396584868431091},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4420171082019806},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35561686754226685},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2936621904373169},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26341432332992554},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.23612725734710693},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/wifs47025.2019.9035110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wifs47025.2019.9035110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Workshop on Information Forensics and Security (WIFS)","raw_type":"proceedings-article"},{"id":"pmh:oai:usiena-air.unisi.it:11365/1105751","is_oa":false,"landing_page_url":"http://hdl.handle.net/11365/1105751","pdf_url":null,"source":{"id":"https://openalex.org/S4377196319","display_name":"Use Siena air (University of Siena)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102064193","host_organization_name":"University of Siena","host_organization_lineage":["https://openalex.org/I102064193"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"mag:3161808919","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002266873181658","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W22271197","https://openalex.org/W1480548253","https://openalex.org/W1972771043","https://openalex.org/W2001412060","https://openalex.org/W2002373723","https://openalex.org/W2009437133","https://openalex.org/W2016828421","https://openalex.org/W2039355449","https://openalex.org/W2055745001","https://openalex.org/W2089649903","https://openalex.org/W2158071928","https://openalex.org/W2170004014","https://openalex.org/W2171810915","https://openalex.org/W2514123796","https://openalex.org/W2729323373","https://openalex.org/W2806156052","https://openalex.org/W2811325011","https://openalex.org/W2903213484","https://openalex.org/W3083319190","https://openalex.org/W3146431904","https://openalex.org/W6628847464","https://openalex.org/W6725340952","https://openalex.org/W6763504945"],"related_works":["https://openalex.org/W3173684497","https://openalex.org/W3190486427","https://openalex.org/W2095511247","https://openalex.org/W2134324324","https://openalex.org/W2913920880","https://openalex.org/W3206974005","https://openalex.org/W1969188281","https://openalex.org/W1992410481","https://openalex.org/W2976672386","https://openalex.org/W1013688086"],"abstract_inverted_index":{"Detecting":[0],"image":[1,170,206],"manipulations":[2,207],"in":[3,17,43,208],"the":[4,31,34,50,56,59,66,74,79,83,119,123,127,132,136,158,165,181,192,195,202,209],"presence":[5,210],"of":[6,33,58,122,131,141,154,167,197,204,211],"JPEG":[7,20],"post-processing":[8],"is":[9,22,69],"often":[10],"a":[11,25,45,90,101,110,142,146,152,168,187,198],"challenging":[12],"task.":[13],"For":[14],"this":[15,86],"reason,":[16],"many":[18],"cases,":[19],"compression":[21],"applied":[23],"as":[24],"laundering-type":[26],"counter-forensic":[27],"attack,":[28],"to":[29,64,93,98,164,185],"impair":[30],"performance":[32],"detector.":[35],"A":[36],"possible":[37,96],"countermeasure,":[38],"for":[39,194,201],"data-driven":[40],"approaches,":[41],"consists":[42],"building":[44],"JPEG-aware":[46,188],"detector":[47,51,75],"by":[48,82,115,135,161],"training":[49,67,105,150],"on":[52,106,145,151],"JPEG-compressed":[53],"images.":[54],"However,":[55],"choice":[57],"quality":[60],"factor":[61],"(QF)":[62],"used":[63,81,134],"compress":[65],"images":[68,107],"not":[70,77],"obvious,":[71],"given":[72],"that":[73],"does":[76],"know":[78],"QF":[80,112,133],"attacker.":[84],"In":[85],"work,":[87],"we":[88],"introduce":[89],"game-theoretic":[91],"framework":[92,160,183],"compare":[94],"three":[95],"approaches":[97],"make":[99],"such":[100],"choice,":[102],"namely:":[103],"i)":[104],"compressed":[108],"using":[109],"single":[111],"chosen":[113],"strategically":[114],"taking":[116],"into":[117],"account":[118],"different":[120],"goals":[121],"forensic":[124],"analyst":[125],"and":[126,138,190],"attacker,":[128],"ii)":[129],"estimation":[130],"attacker":[137],"subsequent":[139],"use":[140,196],"network":[143],"trained":[144],"matched":[147],"QF,":[148],"iii)":[149],"mixture":[153],"QFs.":[155],"We":[156],"exemplify":[157],"proposed":[159,182],"applying":[162],"it":[163],"detection":[166,203],"specific":[169],"manipulation,":[171],"namely":[172],"Adaptive":[173],"Histogram":[174],"Equalization":[175],"(AHE).":[176],"The":[177],"experiments":[178],"show":[179],"how":[180],"allows":[184],"design":[186],"AHE-detector":[189],"set":[191],"stage":[193],"similar":[199],"procedure":[200],"other":[205],"JPEG-laundering":[212],"attacks.":[213]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}