{"id":"https://openalex.org/W2533260366","doi":"https://doi.org/10.1109/wifs.2012.6412647","title":"Decoding fingerprints using the Markov Chain Monte Carlo method","display_name":"Decoding fingerprints using the Markov Chain Monte Carlo method","publication_year":2012,"publication_date":"2012-12-01","ids":{"openalex":"https://openalex.org/W2533260366","doi":"https://doi.org/10.1109/wifs.2012.6412647","mag":"2533260366"},"language":"en","primary_location":{"id":"doi:10.1109/wifs.2012.6412647","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wifs.2012.6412647","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 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/A5062906790","display_name":"Teddy Furon","orcid":"https://orcid.org/0000-0002-1565-765X"},"institutions":[{"id":"https://openalex.org/I4210133778","display_name":"Inria Rennes - Bretagne Atlantique Research Centre","ror":"https://ror.org/04040yw90","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210133778"]},{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en informatique et en automatique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1326498283"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Teddy Furon","raw_affiliation_strings":["INRIA Rennes, Rennes, France"],"affiliations":[{"raw_affiliation_string":"INRIA Rennes, Rennes, France","institution_ids":["https://openalex.org/I4210133778","https://openalex.org/I1326498283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051793615","display_name":"Arnaud Guyader","orcid":null},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en informatique et en automatique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I3124938446","display_name":"Universit\u00e9 Rennes 2","ror":"https://ror.org/01m84wm78","country_code":"FR","type":"education","lineage":["https://openalex.org/I3124938446"]},{"id":"https://openalex.org/I56067802","display_name":"Universit\u00e9 de Rennes","ror":"https://ror.org/015m7wh34","country_code":"FR","type":"education","lineage":["https://openalex.org/I56067802"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Arnaud Guyader","raw_affiliation_strings":["INRIA Rennes, Universite de Rennes II, Rennes, France"],"affiliations":[{"raw_affiliation_string":"INRIA Rennes, Universite de Rennes II, Rennes, France","institution_ids":["https://openalex.org/I3124938446","https://openalex.org/I56067802","https://openalex.org/I1326498283"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079817811","display_name":"Fr\u00e9d\u00e9ric C\u00e9rou","orcid":"https://orcid.org/0000-0002-8752-0492"},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en informatique et en automatique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I4210161663","display_name":"Institut de recherche math\u00e9matique de Rennes","ror":"https://ror.org/05y76vp22","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I2800285241","https://openalex.org/I28221208","https://openalex.org/I3124938446","https://openalex.org/I4210117091","https://openalex.org/I4210141950","https://openalex.org/I4210146044","https://openalex.org/I4210161663","https://openalex.org/I4399657933","https://openalex.org/I56067802","https://openalex.org/I56067802"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Frederic Cerou","raw_affiliation_strings":["INRIA Rennes, IRMAR, Rennes, France"],"affiliations":[{"raw_affiliation_string":"INRIA Rennes, IRMAR, Rennes, France","institution_ids":["https://openalex.org/I4210161663","https://openalex.org/I1326498283"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062906790"],"corresponding_institution_ids":["https://openalex.org/I1326498283","https://openalex.org/I4210133778"],"apc_list":null,"apc_paid":null,"fwci":1.3727,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.84393685,"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":"187","last_page":"192"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9998000264167786,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9998000264167786,"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/T11017","display_name":"Chaos-based Image/Signal Encryption","score":0.9966999888420105,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9952999949455261,"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/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.8079125881195068},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.7903281450271606},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7094616293907166},{"id":"https://openalex.org/keywords/collusion","display_name":"Collusion","score":0.6145731210708618},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.6024483442306519},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5827322006225586},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5466225743293762},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5387780070304871},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.41803228855133057},{"id":"https://openalex.org/keywords/digital-watermarking","display_name":"Digital watermarking","score":0.41649115085601807},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4106009602546692},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2725536823272705},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20515978336334229},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17832398414611816},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15863752365112305},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.06238284707069397}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.8079125881195068},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7903281450271606},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7094616293907166},{"id":"https://openalex.org/C2781198186","wikidata":"https://www.wikidata.org/wiki/Q701521","display_name":"Collusion","level":2,"score":0.6145731210708618},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.6024483442306519},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5827322006225586},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5466225743293762},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5387780070304871},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.41803228855133057},{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.41649115085601807},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4106009602546692},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2725536823272705},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20515978336334229},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17832398414611816},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15863752365112305},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.06238284707069397},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wifs.2012.6412647","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wifs.2012.6412647","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1532272145","https://openalex.org/W1968422945","https://openalex.org/W1977113601","https://openalex.org/W1985093013","https://openalex.org/W1985802463","https://openalex.org/W2031722321","https://openalex.org/W2083594366","https://openalex.org/W2092811336","https://openalex.org/W2102277478","https://openalex.org/W2171717581","https://openalex.org/W4230834613","https://openalex.org/W4292080463","https://openalex.org/W4292691288","https://openalex.org/W6631773883"],"related_works":["https://openalex.org/W3125971950","https://openalex.org/W1580681286","https://openalex.org/W2175355783","https://openalex.org/W2622204791","https://openalex.org/W1579866848","https://openalex.org/W2066716418","https://openalex.org/W2905524938","https://openalex.org/W1546022168","https://openalex.org/W3198356641","https://openalex.org/W2071668645"],"abstract_inverted_index":{"This":[0,70,80,119,171],"paper":[1,81],"proposes":[2],"a":[3,45,56,101,173],"new":[4],"fingerprinting":[5,78,152],"decoder":[6],"based":[7],"on":[8],"the":[9,25,34,38,50,63,84,87,96,109,112,116,122,127,133,136,140,151,161,168,177],"Markov":[10],"Chain":[11],"Monte":[12,57],"Carlo":[13,58],"(MCMC)":[14],"method.":[15,59],"A":[16],"Gibbs":[17],"sampler":[18],"generates":[19],"groups":[20],"of":[21,77,86,103,111,121,135,139,164],"users":[22,30,61],"according":[23],"to":[24,49,100,176],"posterior":[26],"probability":[27,43],"that":[28,44,95,160],"these":[29],"could":[31],"have":[32],"forged":[33],"sequence":[35],"extracted":[36,117],"from":[37,115],"pirated":[39],"content.":[40],"The":[41,60,105,143],"marginal":[42,66],"given":[46],"user":[47],"pertains":[48],"collusion":[51,97,113],"is":[52,82,124,167,172],"then":[53],"estimated":[54],"by":[55],"having":[62],"biggest":[64],"empirical":[65],"probabilities":[67],"are":[68,155],"accused.":[69],"MCMC":[71],"method":[72],"can":[73],"decode":[74],"any":[75],"type":[76],"codes.":[79],"in":[83],"spirit":[85],"`Learn":[88,178],"and":[89,131,179],"Match'":[90,180],"decoding":[91,181],"strategy:":[92],"it":[93],"assumes":[94],"attack":[98],"belongs":[99],"family":[102],"models.":[104],"Expectation-Maximization":[106],"algorithm":[107,123],"estimates":[108],"parameters":[110],"model":[114],"sequence.":[118],"part":[120],"described":[125],"for":[126],"binary":[128],"Tardos":[129],"code":[130,153],"with":[132],"exploitation":[134],"soft":[137],"outputs":[138],"watermarking":[141],"decoder.":[142],"experimental":[144],"body":[145],"considers":[146],"some":[147],"extreme":[148],"setups":[149],"where":[150],"lengths":[154],"very":[156],"small.":[157],"It":[158],"reveals":[159],"weak":[162],"link":[163],"our":[165],"approach":[166],"estimation":[169],"part.":[170],"clear":[174],"warning":[175],"strategy.":[182]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}