{"id":"https://openalex.org/W2545896937","doi":"https://doi.org/10.1109/wifs.2014.7084313","title":"Multiple JPEG compression detection by means of Benford-Fourier coefficients","display_name":"Multiple JPEG compression detection by means of Benford-Fourier coefficients","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W2545896937","doi":"https://doi.org/10.1109/wifs.2014.7084313","mag":"2545896937"},"language":"en","primary_location":{"id":"doi:10.1109/wifs.2014.7084313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wifs.2014.7084313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Workshop on Information Forensics and Security (WIFS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5087688702","display_name":"Cecilia Pasquini","orcid":"https://orcid.org/0000-0002-2125-6983"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Cecilia Pasquini","raw_affiliation_strings":["DISI, University of Trento, Trento, ITALY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DISI, University of Trento, Trento, ITALY","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028899632","display_name":"Giulia Boato","orcid":"https://orcid.org/0000-0002-0260-9528"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giulia Boato","raw_affiliation_strings":["DISI, University of Trento, Trento, ITALY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DISI, University of Trento, Trento, ITALY","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076826398","display_name":"Fernando P\u00e9rez\u2010Gonz\u00e1lez","orcid":"https://orcid.org/0000-0002-0568-1373"},"institutions":[{"id":"https://openalex.org/I6289922","display_name":"Universidade de Vigo","ror":"https://ror.org/05rdf8595","country_code":"ES","type":"education","lineage":["https://openalex.org/I6289922"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Fernando Perez-Gonzalez","raw_affiliation_strings":["EE Telecomunicacion, University of Vigo, Vigo, SPAIN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EE Telecomunicacion, University of Vigo, Vigo, SPAIN","institution_ids":["https://openalex.org/I6289922"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"113","last_page":"118"},"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":0.9757000207901001,"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/T13720","display_name":"Benford\u2019s Law and Fraud Detection","score":0.9746000170707703,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/jpeg","display_name":"JPEG","score":0.8724144697189331},{"id":"https://openalex.org/keywords/lossless-jpeg","display_name":"Lossless JPEG","score":0.7608115673065186},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7193383574485779},{"id":"https://openalex.org/keywords/jpeg-2000","display_name":"JPEG 2000","score":0.6680699586868286},{"id":"https://openalex.org/keywords/transform-coding","display_name":"Transform coding","score":0.6239534616470337},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6163226366043091},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5511595010757446},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5318429470062256},{"id":"https://openalex.org/keywords/compression-artifact","display_name":"Compression artifact","score":0.5141665935516357},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.49362218379974365},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.43793195486068726},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.42257702350616455},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.42222076654434204},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4183327853679657},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4089623689651489},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.32069915533065796},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.30198848247528076},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2986275851726532}],"concepts":[{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.8724144697189331},{"id":"https://openalex.org/C8384606","wikidata":"https://www.wikidata.org/wiki/Q2190356","display_name":"Lossless JPEG","level":5,"score":0.7608115673065186},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193383574485779},{"id":"https://openalex.org/C69216139","wikidata":"https://www.wikidata.org/wiki/Q931783","display_name":"JPEG 2000","level":5,"score":0.6680699586868286},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.6239534616470337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6163226366043091},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5511595010757446},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5318429470062256},{"id":"https://openalex.org/C57654395","wikidata":"https://www.wikidata.org/wiki/Q1097775","display_name":"Compression artifact","level":5,"score":0.5141665935516357},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.49362218379974365},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.43793195486068726},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.42257702350616455},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.42222076654434204},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4183327853679657},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4089623689651489},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.32069915533065796},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.30198848247528076},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2986275851726532},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/wifs.2014.7084313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wifs.2014.7084313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Workshop on Information Forensics and Security (WIFS)","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.unitn.it:11572/100508","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/100508","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W200526583","https://openalex.org/W1983489542","https://openalex.org/W1994743750","https://openalex.org/W1997127867","https://openalex.org/W2003158159","https://openalex.org/W2019841176","https://openalex.org/W2049771774","https://openalex.org/W2059907896","https://openalex.org/W2089454561","https://openalex.org/W2096933452","https://openalex.org/W2111280862","https://openalex.org/W2130225759","https://openalex.org/W2148610715","https://openalex.org/W2432926394","https://openalex.org/W2534080848","https://openalex.org/W2540224028","https://openalex.org/W2541429634","https://openalex.org/W3148833453","https://openalex.org/W4238456558","https://openalex.org/W6676669043"],"related_works":["https://openalex.org/W3190486427","https://openalex.org/W4243959093","https://openalex.org/W1998280942","https://openalex.org/W1992410481","https://openalex.org/W2441603424","https://openalex.org/W2026465795","https://openalex.org/W2145138541","https://openalex.org/W3137515556","https://openalex.org/W2545896937","https://openalex.org/W2111280862"],"abstract_inverted_index":{"The":[0,58,100],"analysis":[1],"of":[2,8,17,42,53,82,95],"JPEG":[3,48,73,86],"compressed":[4],"images":[5,49],"is":[6,98],"one":[7],"the":[9,18,22,40,51,54,80,92],"most":[10,107],"studied":[11],"problems":[12],"in":[13,47,79,106],"image":[14,97],"forensics,":[15],"because":[16],"extensive":[19],"use":[20],"and":[21,50,66,84],"characteristic":[23],"traces":[24],"left":[25],"by":[26],"such":[27],"coding":[28],"operation.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33],"propose":[34],"a":[35],"novel":[36],"statistical":[37],"framework":[38],"for":[39],"identification":[41],"previous":[43],"multiple":[44],"aligned":[45],"compressions":[46,74],"estimation":[52],"quality":[55,90],"factors":[56],"applied.":[57],"method":[59],"has":[60],"been":[61],"tested":[62],"on":[63],"different":[64,89],"datasets":[65],"forensic":[67],"scenarios,":[68],"where":[69],"up":[70],"to":[71,113],"three":[72],"are":[75],"considered.":[76],"Moreover,":[77],"both":[78],"case":[81],"double":[83],"triple":[85],"encoding":[87],"with":[88,111],"factors,":[91],"compression":[93],"history":[94],"each":[96],"estimated.":[99],"experiments":[101],"show":[102],"good":[103],"performance":[104],"and,":[105],"cases,":[108],"higher":[109],"accuracies":[110],"respect":[112],"state-of-the-art":[114],"methods.":[115]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}