{"id":"https://openalex.org/W2417217221","doi":"https://doi.org/10.1145/2909827.2930803","title":"Boosting Steganalysis with Explicit Feature Maps","display_name":"Boosting Steganalysis with Explicit Feature Maps","publication_year":2016,"publication_date":"2016-06-10","ids":{"openalex":"https://openalex.org/W2417217221","doi":"https://doi.org/10.1145/2909827.2930803","mag":"2417217221"},"language":"en","primary_location":{"id":"doi:10.1145/2909827.2930803","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2909827.2930803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th ACM Workshop on Information Hiding and Multimedia 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/A5075476512","display_name":"Mehdi Boroumand","orcid":"https://orcid.org/0000-0002-7798-0671"},"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":"Mehdi Boroumand","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"]}]},{"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":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I123946342"],"apc_list":null,"apc_paid":null,"fwci":0.9058,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.8686302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"149","last_page":"157"},"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":0.9991999864578247,"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":0.9922000169754028,"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":0.9589712023735046},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.8427748680114746},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6561020016670227},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6420286297798157},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6147639751434326},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5473133325576782},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4670718312263489},{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.46528521180152893},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.1412825584411621}],"concepts":[{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.9589712023735046},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8427748680114746},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6561020016670227},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6420286297798157},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6147639751434326},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5473133325576782},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4670718312263489},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.46528521180152893},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.1412825584411621},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2909827.2930803","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2909827.2930803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th ACM Workshop on Information Hiding and Multimedia Security","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1422592601","https://openalex.org/W1560724230","https://openalex.org/W1658688950","https://openalex.org/W1963536592","https://openalex.org/W1973466159","https://openalex.org/W1976570511","https://openalex.org/W1979931042","https://openalex.org/W2009130368","https://openalex.org/W2038597090","https://openalex.org/W2040299224","https://openalex.org/W2041356996","https://openalex.org/W2045110448","https://openalex.org/W2054408106","https://openalex.org/W2055625960","https://openalex.org/W2059019537","https://openalex.org/W2063442212","https://openalex.org/W2071451750","https://openalex.org/W2104705565","https://openalex.org/W2109235804","https://openalex.org/W2124664712","https://openalex.org/W2147898188","https://openalex.org/W2167999072","https://openalex.org/W2192227561","https://openalex.org/W2339370745","https://openalex.org/W2398416088","https://openalex.org/W2538511122","https://openalex.org/W2541922885","https://openalex.org/W2542290803","https://openalex.org/W2545241995","https://openalex.org/W2545848843","https://openalex.org/W2548753991","https://openalex.org/W2579698629"],"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":{"Explicit":[0],"non-linear":[1,27,76],"transformations":[2,28],"of":[3,35,57,106,129],"existing":[4,19,107],"steganalysis":[5],"features":[6,37],"are":[7,29],"shown":[8],"to":[9,13,68,119,127,136],"boost":[10],"their":[11],"ability":[12],"detect":[14],"steganography":[15],"in":[16],"combination":[17],"with":[18,45,53,134],"simple":[20],"classifiers,":[21],"such":[22],"as":[23,110],"the":[24,54,58,63,75,81,92,104,122,137],"FLD-ensemble.":[25],"The":[26,48,113],"learned":[30],"from":[31],"a":[32,88,96],"small":[33],"number":[34],"cover":[36,82],"using":[38],"Nystr\u00f6m":[39],"approximation":[40],"on":[41,80],"pilot":[42],"vectors":[43],"obtained":[44],"kernelized":[46],"PCA.":[47],"best":[49],"performance":[50,132],"is":[51,95],"achieved":[52],"exponential":[55],"form":[56],"Hellinger":[59],"kernel,":[60],"which":[61],"improves":[62],"detection":[64],"accuracy":[65,105],"by":[66],"up":[67,126],"2-3%":[69],"for":[70,102],"spatial-domain":[71],"contentadaptive":[72],"steganography.":[73],"Since":[74],"map":[77,114],"depends":[78],"only":[79],"source":[83],"and":[84,98],"its":[85],"learning":[86],"has":[87],"low":[89,99],"computational":[90],"complexity,":[91],"proposed":[93],"approach":[94],"practical":[97],"cost":[100],"method":[101],"boosting":[103],"detectors":[108],"built":[109],"binary":[111],"classifiers.":[112],"can":[115],"also":[116],"be":[117],"used":[118],"significantly":[120],"reduce":[121],"feature":[123],"dimensionality":[124],"(by":[125],"factor":[128],"ten)":[130],"without":[131],"loss":[133],"respect":[135],"non-transformed":[138],"features.":[139]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":5},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
