{"id":"https://openalex.org/W2292697315","doi":"https://doi.org/10.1109/apsipa.2015.7415374","title":"A new detector of LSB matching steganography based on likelihood ratio test for multivariate Gaussian covers","display_name":"A new detector of LSB matching steganography based on likelihood ratio test for multivariate Gaussian covers","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2292697315","doi":"https://doi.org/10.1109/apsipa.2015.7415374","mag":"2292697315"},"language":"en","primary_location":{"id":"doi:10.1109/apsipa.2015.7415374","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2015.7415374","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","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/A5112492919","display_name":"Guangyuan Yang","orcid":"https://orcid.org/0000-0002-0917-8513"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guangyuan Yang","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100371548","display_name":"Xiaolong Li","orcid":"https://orcid.org/0000-0002-6111-9000"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolong Li","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365163","display_name":"Bin Li","orcid":"https://orcid.org/0000-0002-2613-5451"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Li","raw_affiliation_strings":["College of Information Engineering, Shenzhen University, Shenzhen, GD, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shenzhen University, Shenzhen, GD, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001396675","display_name":"Zongming Guo","orcid":"https://orcid.org/0000-0002-4944-9621"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongming Guo","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112492919"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.1841,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60954407,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"6985","issue":null,"first_page":"757","last_page":"760"},"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":0.9991000294685364,"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/T10828","display_name":"Biometric Identification and Security","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9250278472900391},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7421112060546875},{"id":"https://openalex.org/keywords/least-significant-bit","display_name":"Least significant bit","score":0.7194958329200745},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6492726802825928},{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.6472007036209106},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5765591859817505},{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.5593516230583191},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5436609983444214},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5090243816375732},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5031585097312927},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4994478225708008},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.48865893483161926},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4539213180541992},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.4117226302623749},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3759966492652893},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3747364282608032},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37429744005203247},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2544950246810913},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.10824427008628845},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10598117113113403},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08086410164833069}],"concepts":[{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.9250278472900391},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7421112060546875},{"id":"https://openalex.org/C4305246","wikidata":"https://www.wikidata.org/wiki/Q3885225","display_name":"Least significant bit","level":2,"score":0.7194958329200745},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6492726802825928},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.6472007036209106},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5765591859817505},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.5593516230583191},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5436609983444214},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5090243816375732},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5031585097312927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4994478225708008},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.48865893483161926},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4539213180541992},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.4117226302623749},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3759966492652893},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3747364282608032},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37429744005203247},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2544950246810913},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.10824427008628845},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10598117113113403},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08086410164833069},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipa.2015.7415374","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2015.7415374","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","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":18,"referenced_works":["https://openalex.org/W10162706","https://openalex.org/W22271197","https://openalex.org/W29803638","https://openalex.org/W1459587671","https://openalex.org/W1969171557","https://openalex.org/W2000251700","https://openalex.org/W2000829573","https://openalex.org/W2004686575","https://openalex.org/W2007994675","https://openalex.org/W2027272619","https://openalex.org/W2076312302","https://openalex.org/W2085924571","https://openalex.org/W2089860099","https://openalex.org/W2101954717","https://openalex.org/W2153615901","https://openalex.org/W2164027883","https://openalex.org/W6600894407","https://openalex.org/W6628582309"],"related_works":["https://openalex.org/W2148973528","https://openalex.org/W2939392096","https://openalex.org/W4243922849","https://openalex.org/W2205085860","https://openalex.org/W2134958869","https://openalex.org/W2977151837","https://openalex.org/W2059133021","https://openalex.org/W2771684231","https://openalex.org/W2158736088","https://openalex.org/W4297776738"],"abstract_inverted_index":{"Recently,":[0],"steganalysis":[1],"based":[2,63],"on":[3,64],"hypothesis":[4],"test":[5],"theory":[6],"becomes":[7],"a":[8,28,56],"focus.":[9],"However,":[10],"the":[11,41,73,78,89],"correlation":[12],"between":[13],"adjacent":[14],"pixels":[15,48,81],"is":[16,21,38,61,84],"not":[17,23],"exploited":[18],"and":[19,55,82],"this":[20,26,83],"obviously":[22],"reasonable.":[24],"In":[25],"paper,":[27],"new":[29,57],"detector":[30,58,74],"for":[31,59,87],"least":[32],"significant":[33],"bit":[34],"matching":[35],"(LSBM)":[36],"steganography":[37],"proposed":[39],"with":[40],"consideration":[42],"of":[43],"pixel":[44],"correlation.":[45],"The":[46],"cover":[47],"are":[49],"modeled":[50],"by":[51,75],"multivariate":[52],"Gaussian":[53],"distribution":[54],"LSBM":[60],"derived":[62],"likelihood":[65],"ratio":[66],"test.":[67],"Moreover,":[68],"we":[69],"propose":[70],"to":[71],"calculate":[72],"considering":[76],"only":[77],"smooth":[79],"image":[80],"very":[85],"helpful":[86],"improving":[88],"detection":[90],"performance.":[91]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
