{"id":"https://openalex.org/W2009490298","doi":"https://doi.org/10.1145/1411328.1411357","title":"Novelty detection in blind steganalysis","display_name":"Novelty detection in blind steganalysis","publication_year":2008,"publication_date":"2008-09-22","ids":{"openalex":"https://openalex.org/W2009490298","doi":"https://doi.org/10.1145/1411328.1411357","mag":"2009490298"},"language":"en","primary_location":{"id":"doi:10.1145/1411328.1411357","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1411328.1411357","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM workshop on Multimedia and security","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/A5059337672","display_name":"Tom\u00e1\u0161 Pevn\u00fd","orcid":"https://orcid.org/0000-0002-5768-9713"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Tom\u00e1\u0161 Pevn\u00fd","raw_affiliation_strings":["INPG - Gipsa-Lab, Grenoble cedex, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INPG - Gipsa-Lab, Grenoble cedex, France","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I4210124956","https://openalex.org/I899635006"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081020569","display_name":"Jessica Fridrich","orcid":"https://orcid.org/0009-0003-6516-628X"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jessica Fridrich","raw_affiliation_strings":["Binghamton University, Binghamton, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Binghamton University, Binghamton, NY, USA","institution_ids":["https://openalex.org/I123946342"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8674,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.92514013,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"167","last_page":"176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","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/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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9988999962806702,"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/steganalysis","display_name":"Steganalysis","score":0.9317951202392578},{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.9110952615737915},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7073310613632202},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7049087285995483},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7038600444793701},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6802379488945007},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.538054883480072},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.49336281418800354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45243245363235474},{"id":"https://openalex.org/keywords/novelty-detection","display_name":"Novelty detection","score":0.4473867416381836},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.4080314338207245},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39585310220718384}],"concepts":[{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.9317951202392578},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.9110952615737915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7073310613632202},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7049087285995483},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7038600444793701},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6802379488945007},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.538054883480072},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.49336281418800354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45243245363235474},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.4473867416381836},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.4080314338207245},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39585310220718384},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1411328.1411357","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1411328.1411357","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM workshop on Multimedia and security","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":27,"referenced_works":["https://openalex.org/W1512190422","https://openalex.org/W1518402653","https://openalex.org/W1525451064","https://openalex.org/W1527181506","https://openalex.org/W1531128672","https://openalex.org/W1534147215","https://openalex.org/W1560724230","https://openalex.org/W1760530029","https://openalex.org/W1765283245","https://openalex.org/W1806317803","https://openalex.org/W1875845630","https://openalex.org/W2049562124","https://openalex.org/W2052389107","https://openalex.org/W2085820558","https://openalex.org/W2091459879","https://openalex.org/W2103387009","https://openalex.org/W2132870739","https://openalex.org/W2142604419","https://openalex.org/W2151996692","https://openalex.org/W2155447586","https://openalex.org/W2167717760","https://openalex.org/W2167999072","https://openalex.org/W2561675875","https://openalex.org/W2611745365","https://openalex.org/W2913153438","https://openalex.org/W3003808604","https://openalex.org/W6638363521"],"related_works":["https://openalex.org/W2148973528","https://openalex.org/W2939392096","https://openalex.org/W4243922849","https://openalex.org/W2106726851","https://openalex.org/W4309385482","https://openalex.org/W3154843532","https://openalex.org/W2068740952","https://openalex.org/W2182496537","https://openalex.org/W2792878404","https://openalex.org/W1965039524"],"abstract_inverted_index":{"It":[0],"is":[1,33,63],"generally":[2,129],"believed":[3],"that":[4,21,59],"a":[5,34,70,120],"blind":[6],"steganalyzer":[7],"trained":[8],"on":[9,51,119,135,147,170,181],"sufficiently":[10],"many":[11],"diverse":[12],"steganographic":[13,124],"algorithms":[14,163],"will":[15,23],"become":[16],"universal":[17,103],"in":[18],"the":[19,39,43,49,53,61,80,138,182],"sense":[20],"it":[22,75],"generalize":[24],"to":[25,78,157,159],"previously":[26,148],"unseen":[27,149],"(novel)":[28],"stego":[29,66,83,150,162,172],"methods.":[30,173],"While":[31],"this":[32,94],"partially":[35],"correct":[36],"statement":[37],"if":[38,60],"embedding":[40,73],"mechanism":[41],"of":[42,48,102,123,140,176],"novel":[44],"method":[45],"resembles":[46],"some":[47],"methods":[50,153],"which":[52],"classifier":[54,62],"was":[55],"trained,":[56],"we":[57,96],"demonstrate":[58],"presented":[64],"with":[65],"images":[67,81],"produced":[68],"by":[69,93],"completely":[71],"different":[72],"mechanism,":[74],"may":[76,144],"fail":[77,145,158],"detect":[79,160],"as":[82],"even":[84],"for":[85,100],"an":[86],"otherwise":[87],"fairly":[88],"easily":[89],"detectable":[90],"method.":[91],"Motivated":[92],"observation,":[95],"explore":[97],"two":[98],"approaches":[99,133],"construction":[101],"steganalyzers":[104],"-":[105],"one-class":[106],"and":[107,112,116],"one-against-all":[108],"classifiers.":[109],"Their":[110],"advantages":[111],"disadvantages":[113],"are":[114,154],"discussed":[115],"performance":[117,131],"compared":[118],"wide":[121],"variety":[122],"algorithms.":[125,151],"One-against-all":[126],"classifiers":[127],"have":[128,165],"better":[130],"than":[132],"based":[134],"characterizing":[136],"just":[137],"class":[139],"covers":[141],"but":[142,164],"they":[143],"catastrophically":[146],"One-class":[152],"less":[155],"likely":[156],"unknown":[161],"lower":[166],"overall":[167],"detection":[168],"accuracy":[169],"known":[171],"The":[174],"suitability":[175],"each":[177],"approach":[178],"thus":[179],"depends":[180],"application.":[183]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}