{"id":"https://openalex.org/W4200116352","doi":"https://doi.org/10.1109/wifs53200.2021.9648385","title":"Source Attribution of Online News Images by Compression Analysis","display_name":"Source Attribution of Online News Images by Compression Analysis","publication_year":2021,"publication_date":"2021-12-07","ids":{"openalex":"https://openalex.org/W4200116352","doi":"https://doi.org/10.1109/wifs53200.2021.9648385"},"language":"en","primary_location":{"id":"doi:10.1109/wifs53200.2021.9648385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wifs53200.2021.9648385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5049429852","display_name":"Michael Albright","orcid":"https://orcid.org/0000-0003-1778-6495"},"institutions":[{"id":"https://openalex.org/I74786994","display_name":"Kitware (United States)","ror":"https://ror.org/02s2acn37","country_code":"US","type":"company","lineage":["https://openalex.org/I74786994"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Albright","raw_affiliation_strings":["Kitware, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kitware, Inc","institution_ids":["https://openalex.org/I74786994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088457325","display_name":"Nitesh Menon","orcid":null},"institutions":[{"id":"https://openalex.org/I74786994","display_name":"Kitware (United States)","ror":"https://ror.org/02s2acn37","country_code":"US","type":"company","lineage":["https://openalex.org/I74786994"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nitesh Menon","raw_affiliation_strings":["Kitware, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kitware, Inc","institution_ids":["https://openalex.org/I74786994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038782810","display_name":"Kristy Roschke","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kristy Roschke","raw_affiliation_strings":["Arizona State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039530454","display_name":"Arslan Basharat","orcid":null},"institutions":[{"id":"https://openalex.org/I74786994","display_name":"Kitware (United States)","ror":"https://ror.org/02s2acn37","country_code":"US","type":"company","lineage":["https://openalex.org/I74786994"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arslan Basharat","raw_affiliation_strings":["Kitware, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kitware, Inc","institution_ids":["https://openalex.org/I74786994"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0955,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40376876,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"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":0.9672999978065491,"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":0.9262999892234802,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8095698952674866},{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.5057728290557861},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.48086339235305786},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.468142569065094},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.46041423082351685},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44725683331489563},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4461883306503296},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.39748862385749817},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34902164340019226},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3468281626701355},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1381700038909912}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8095698952674866},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.5057728290557861},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.48086339235305786},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.468142569065094},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.46041423082351685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44725683331489563},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4461883306503296},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39748862385749817},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34902164340019226},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3468281626701355},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1381700038909912},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wifs53200.2021.9648385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wifs53200.2021.9648385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Workshop on Information Forensics and Security (WIFS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G5771177262","display_name":null,"funder_award_id":"HR001120C0123","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":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2036124729","https://openalex.org/W2116380715","https://openalex.org/W2295598076","https://openalex.org/W2394485828","https://openalex.org/W2582467130","https://openalex.org/W2786279313","https://openalex.org/W2786921035","https://openalex.org/W2902674081","https://openalex.org/W2903453184","https://openalex.org/W2921916843","https://openalex.org/W2942374856","https://openalex.org/W2993503428","https://openalex.org/W3028935322","https://openalex.org/W3103287961","https://openalex.org/W3164725880"],"related_works":["https://openalex.org/W2948148442","https://openalex.org/W2461250372","https://openalex.org/W2394342941","https://openalex.org/W2169853506","https://openalex.org/W2547124190","https://openalex.org/W2350586049","https://openalex.org/W2385628723","https://openalex.org/W2057878850","https://openalex.org/W2169871401","https://openalex.org/W3008492011"],"abstract_inverted_index":{"The":[0,122],"rapid":[1],"increase":[2],"in":[3,68,157,178],"the":[4,59,69,73,87,99,153,179],"amount":[5],"of":[6,20,28,40,72,109],"online":[7,60],"disinformation":[8],"warrants":[9],"new":[10],"and":[11,65,81,95,138,169],"robust":[12],"digital":[13],"forensics":[14],"methods":[15],"for":[16,31,91,135,161],"validating":[17],"purported":[18],"sources":[19,143],"multimodal":[21],"news":[22,29,61,92,120,142],"articles.":[23],"We":[24,77,97],"conducted":[25],"a":[26,106,165],"survey":[27],"photojournalists":[30],"insights":[32],"into":[33],"their":[34],"workflows.":[35],"A":[36],"high":[37],"percentage":[38],"(91%)":[39],"respondents":[41],"reported":[42],"standardized":[43],"photo":[44],"publishing":[45],"procedures,":[46],"which":[47],"we":[48,56,144],"hypothesize":[49],"facilitates":[50],"source":[51,93,136,162],"verification.":[52,139],"In":[53],"this":[54],"work,":[55],"demonstrate":[57],"that":[58],"sites":[62],"leave":[63],"predictable":[64],"discernible":[66],"patterns":[67],"compression":[70,89,124],"settings":[71],"images":[74,112],"they":[75],"publish.":[76],"propose":[78],"novel,":[79],"simple,":[80],"very":[82,149],"efficient":[83],"algorithms":[84,155],"to":[85,147],"analyze":[86],"image":[88,123],"profiles":[90],"verification":[94,163],"identification.":[96],"evaluate":[98],"algorithms'":[100],"effectiveness":[101],"through":[102],"extensive":[103],"experiments":[104],"on":[105],"newly-released":[107],"dataset":[108],"over":[110,114],"64K":[111],"from":[113,118],"34K":[115],"articles":[116],"collected":[117],"30":[119],"sites.":[121],"features":[125],"are":[126,145],"modeled":[127],"by":[128],"Naive":[129],"Bayes":[130],"variants":[131],"or":[132],"XGBoost":[133],"classifiers":[134],"attribution":[137],"For":[140],"these":[141],"able":[146],"achieve":[148],"strong":[150],"performance":[151],"with":[152,174],"proposed":[154],"resulting":[156],"0.92\u20130.94":[158],"average":[159,180],"AUC":[160],"under":[164],"closed":[166],"set":[167,172],"scenario,":[168],"compelling":[170],"open":[171],"generalization":[173],"only":[175],"0.0\u20130.04":[176],"reduction":[177],"AUC.":[181]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}