{"id":"https://openalex.org/W2608835720","doi":"https://doi.org/10.1109/icpr.2016.7900302","title":"Selection of robust features for the Cover Source Mismatch problem in 3D steganalysis","display_name":"Selection of robust features for the Cover Source Mismatch problem in 3D steganalysis","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2608835720","doi":"https://doi.org/10.1109/icpr.2016.7900302","mag":"2608835720"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7900302","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900302","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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/A5100330760","display_name":"Zhenyu Li","orcid":"https://orcid.org/0000-0002-4852-5055"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Zhenyu Li","raw_affiliation_strings":["Department of Computer Science, University of York, York, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of York, York, UK","institution_ids":["https://openalex.org/I52099693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002932489","display_name":"Adrian G. Bor\u015f","orcid":"https://orcid.org/0000-0001-7838-0021"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Adrian G. Bors","raw_affiliation_strings":["Department of Computer Science, University of York, York, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of York, York, UK","institution_ids":["https://openalex.org/I52099693"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100330760"],"corresponding_institution_ids":["https://openalex.org/I52099693"],"apc_list":null,"apc_paid":null,"fwci":1.3516,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.87693474,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4256","last_page":"4261"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","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/T12357","display_name":"Digital Media Forensic Detection","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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9945999979972839,"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/steganalysis","display_name":"Steganalysis","score":0.9156224727630615},{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.7533175945281982},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7034082412719727},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6807752251625061},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6693867444992065},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.6420634984970093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5013313293457031},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44884711503982544},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.41916191577911377},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3788183331489563},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.2794915437698364},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11414727568626404}],"concepts":[{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.9156224727630615},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.7533175945281982},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7034082412719727},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6807752251625061},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6693867444992065},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.6420634984970093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5013313293457031},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44884711503982544},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.41916191577911377},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3788183331489563},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.2794915437698364},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11414727568626404},{"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2016.7900302","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900302","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:127771","is_oa":false,"landing_page_url":"https://orcid.org/0000-0001-7838-0021>","pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"NonPeerReviewed"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W22271197","https://openalex.org/W1495061682","https://openalex.org/W1580817707","https://openalex.org/W1590456553","https://openalex.org/W1658688950","https://openalex.org/W1713630528","https://openalex.org/W1964254008","https://openalex.org/W1981833647","https://openalex.org/W1986450485","https://openalex.org/W1992159937","https://openalex.org/W1995716398","https://openalex.org/W2001011421","https://openalex.org/W2030997406","https://openalex.org/W2041356996","https://openalex.org/W2043896016","https://openalex.org/W2050204708","https://openalex.org/W2063442212","https://openalex.org/W2065379506","https://openalex.org/W2087953725","https://openalex.org/W2101079470","https://openalex.org/W2124664712","https://openalex.org/W2131711692","https://openalex.org/W2149454242","https://openalex.org/W2154053567","https://openalex.org/W2156504490","https://openalex.org/W2161226201","https://openalex.org/W2167101736","https://openalex.org/W2170311913","https://openalex.org/W2293496905","https://openalex.org/W2396870857","https://openalex.org/W2405358909","https://openalex.org/W2997674406","https://openalex.org/W2998216295","https://openalex.org/W4230163235","https://openalex.org/W4285719527","https://openalex.org/W6649317872","https://openalex.org/W6658391760","https://openalex.org/W6660863743","https://openalex.org/W6682496738","https://openalex.org/W6682686508","https://openalex.org/W6713717136","https://openalex.org/W7066667914"],"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/W2068740952","https://openalex.org/W1583147569","https://openalex.org/W2182496537","https://openalex.org/W2792878404","https://openalex.org/W3154843532"],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"a":[3,15,35,49,53,88],"novel":[4],"method":[5,129],"for":[6,156],"extracting":[7],"sets":[8,221],"of":[9,55,62,90,113,203,210,222],"feature":[10],"from":[11,58,97,191],"3D":[12,63,91,134,176],"objects":[13,64,92,122,143,177],"characterising":[14],"robust":[16,167,204],"steganalyzer.":[17],"Specifically,":[18],"the":[19,24,68,73,76,101,104,110,114,120,139,162,196,200,211,215],"proposed":[20,166],"steganalyzer":[21,31,46,77,115],"should":[22],"mitigate":[23],"Cover":[25],"Source":[26],"Mismatch":[27],"(CSM)":[28],"paradigm.":[29],"A":[30,45],"is":[32,170],"considered":[33],"as":[34,48,65,179],"classifier":[36,50],"aiming":[37],"to":[38,80,108,131,154,219],"identify":[39,81],"separately":[40],"cover":[41,59,121],"and":[42,149,185],"stego":[43,60],"objects.":[44],"behaves":[47],"by":[51,144,182],"considering":[52,173],"set":[54,89,202],"features":[56,135,205],"extracted":[57],"pairs":[61],"inputs":[66],"during":[67,72,100],"training":[69,163],"stage.":[70],"However,":[71],"testing":[74,109],"stage,":[75],"would":[78],"have":[79],"whether":[82],"specific":[83],"information":[84,125,147],"was":[85],"hidden":[86],"in":[87,119,142,161,175,214],"which":[93],"can":[94],"be":[95],"different":[96,157],"those":[98,133,180],"used":[99],"training.":[102],"Addressing":[103],"CSM":[105],"paradigm":[106],"corresponds":[107],"generalization":[111],"ability":[112],"when":[116,172,217],"introducing":[117],"distortions":[118],"before":[123],"hiding":[124,148],"through":[126],"steganography.":[127],"Our":[128],"aims":[130],"select":[132],"that":[136,195],"model":[137],"best":[138],"changes":[140,174,212],"introduced":[141],"steganography":[145],"or":[146],"moreover":[150],"they":[151],"are":[152],"able":[153],"generalize":[155],"objects,":[158,216],"not":[159],"present":[160],"set.":[164],"The":[165,188],"steganalysis":[168],"approach":[169],"tested":[171],"such":[178],"produced":[181],"mesh":[183],"simplification":[184],"additive":[186],"noise.":[187],"results":[189],"obtained":[190],"this":[192],"study":[193],"show":[194],"steganalyzers":[197],"trained":[198],"with":[199],"selected":[201],"achieve":[206],"better":[207],"detection":[208],"accuracy":[209],"embedded":[213],"compared":[218],"other":[220],"features.":[223]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}