{"id":"https://openalex.org/W2039719331","doi":"https://doi.org/10.1109/fskd.2014.6980939","title":"Locating steganographic payloads by combining weighed-stego residuals and maximum a posteriori probability cover estimator","display_name":"Locating steganographic payloads by combining weighed-stego residuals and maximum a posteriori probability cover estimator","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W2039719331","doi":"https://doi.org/10.1109/fskd.2014.6980939","mag":"2039719331"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2014.6980939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2014.6980939","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","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/A5101999100","display_name":"Tao Zhang","orcid":"https://orcid.org/0000-0002-2639-4357"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tao Zhang","raw_affiliation_strings":["Zhengzhou Information Science and Technology, Institute Zhengzhou, China","Zhengzhou Information Science and Technology Institute Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou Information Science and Technology, Institute Zhengzhou, China","institution_ids":[]},{"raw_affiliation_string":"Zhengzhou Information Science and Technology Institute Zhengzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050822798","display_name":"Xiaomeng Yan","orcid":"https://orcid.org/0000-0002-6375-6310"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaomeng Yan","raw_affiliation_strings":["Zhengzhou Information Science and Technology, Institute Zhengzhou, China","Zhengzhou Information Science and Technology Institute Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou Information Science and Technology, Institute Zhengzhou, China","institution_ids":[]},{"raw_affiliation_string":"Zhengzhou Information Science and Technology Institute Zhengzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101999100"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.10686969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1768","issue":null,"first_page":"798","last_page":"802"},"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":0.9994000196456909,"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":0.9976999759674072,"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/steganography","display_name":"Steganography","score":0.7475482821464539},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.6496630311012268},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.6374273896217346},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6242100596427917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5626583099365234},{"id":"https://openalex.org/keywords/payload","display_name":"Payload (computing)","score":0.5374166965484619},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5220094323158264},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5178449749946594},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.49881744384765625},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4563212990760803},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.37407541275024414},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37125664949417114},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.35782936215400696},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.355449914932251},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.3191356956958771},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10542193055152893}],"concepts":[{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.7475482821464539},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.6496630311012268},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.6374273896217346},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6242100596427917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5626583099365234},{"id":"https://openalex.org/C134066672","wikidata":"https://www.wikidata.org/wiki/Q1424639","display_name":"Payload (computing)","level":3,"score":0.5374166965484619},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5220094323158264},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5178449749946594},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.49881744384765625},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4563212990760803},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.37407541275024414},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37125664949417114},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.35782936215400696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.355449914932251},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.3191356956958771},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10542193055152893},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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:10.1109/fskd.2014.6980939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2014.6980939","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","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":15,"referenced_works":["https://openalex.org/W1589812914","https://openalex.org/W1969171557","https://openalex.org/W1973941018","https://openalex.org/W2037956730","https://openalex.org/W2075652908","https://openalex.org/W2078125794","https://openalex.org/W2086478500","https://openalex.org/W2099343788","https://openalex.org/W2124890704","https://openalex.org/W2138222530","https://openalex.org/W2156926681","https://openalex.org/W2576355915","https://openalex.org/W6635090181","https://openalex.org/W6642145819","https://openalex.org/W6674726021"],"related_works":["https://openalex.org/W4377927309","https://openalex.org/W3217722139","https://openalex.org/W4210899600","https://openalex.org/W1503532423","https://openalex.org/W2150865841","https://openalex.org/W1967494390","https://openalex.org/W3013496002","https://openalex.org/W2465363361","https://openalex.org/W2169353922","https://openalex.org/W4284711868"],"abstract_inverted_index":{"For":[0],"the":[1,17,21,30,41,48,70,76,86,91,97,102,108],"least":[2],"significant":[3],"bit":[4],"(LSB)":[5],"repalcement":[6],"steganography,":[7],"an":[8],"improved":[9,49],"cover":[10,27,51,63],"estimation":[11,52,64],"method":[12,53,88],"is":[13,45,72],"proposed":[14,87],"by":[15],"combining":[16],"weighted-stego(WS)":[18],"residuals":[19,32],"and":[20],"maximum":[22],"a":[23,55,60,114],"posteriori":[24],"probability":[25],"(MAP)":[26],"estimator.":[28],"First,":[29],"WS":[31],"are":[33],"used":[34],"to":[35,47,74],"perform":[36],"preliminary":[37,42],"payload":[38,78,94],"location.":[39],"Next,":[40],"location":[43,79,95],"result":[44],"applied":[46],"MAP":[50],"as":[54],"priori":[56],"information":[57],"so":[58],"that":[59,85],"more":[61],"accurate":[62],"algorithm":[65],"will":[66],"be":[67],"obtained.":[68],"Finally,":[69],"residual":[71],"computed":[73],"derive":[75],"final":[77],"result.":[80],"Previous":[81],"experiments":[82],"have":[83],"proved":[84],"can":[89],"improve":[90],"accuracy":[92],"of":[93],"for":[96,100,117],"LSB":[98],"replacement":[99],"either":[101],"spatial":[103],"domain":[104],"BMP":[105],"image":[106],"or":[107],"JPEG":[109],"decompression":[110],"image.":[111],"It":[112],"has":[113],"good":[115],"robustness":[116],"different":[118],"embedding":[119],"rates.":[120]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}