{"id":"https://openalex.org/W2565257220","doi":"https://doi.org/10.1109/tifs.2017.2779446","title":"Large-Scale JPEG Image Steganalysis Using Hybrid Deep-Learning Framework","display_name":"Large-Scale JPEG Image Steganalysis Using Hybrid Deep-Learning Framework","publication_year":2017,"publication_date":"2017-12-04","ids":{"openalex":"https://openalex.org/W2565257220","doi":"https://doi.org/10.1109/tifs.2017.2779446","mag":"2565257220"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2017.2779446","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2017.2779446","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1611.03233","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061167775","display_name":"Jishen Zeng","orcid":"https://orcid.org/0000-0002-4894-9966"},"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":true,"raw_author_name":"Jishen Zeng","raw_affiliation_strings":["College of Information Engineering, Shenzhen University, Shenzhen, China","Shenzhen Key Laboratory of Media Security, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Shenzhen Key Laboratory of Media Security, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023503629","display_name":"Shunquan Tan","orcid":"https://orcid.org/0000-0002-7457-3691"},"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":"Shunquan Tan","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","Shenzhen Key Laboratory of Media Security, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Shenzhen Key Laboratory of Media Security, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"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, China","Shenzhen Key Laboratory of Media Security, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Shenzhen Key Laboratory of Media Security, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047964483","display_name":"Jiwu Huang","orcid":"https://orcid.org/0000-0002-7625-5689"},"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":"Jiwu Huang","raw_affiliation_strings":["College of Information Engineering, Shenzhen University, Shenzhen, China","Shenzhen Key Laboratory of Media Security, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Shenzhen Key Laboratory of Media Security, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061167775"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":10.6304,"has_fulltext":false,"cited_by_count":217,"citation_normalized_percentile":{"value":0.9885863,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"13","issue":"5","first_page":"1200","last_page":"1214"},"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":0.9997000098228455,"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":0.9965000152587891,"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":0.8739058375358582},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8177935481071472},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6701008081436157},{"id":"https://openalex.org/keywords/jpeg","display_name":"JPEG","score":0.6373500227928162},{"id":"https://openalex.org/keywords/jpeg-2000","display_name":"JPEG 2000","score":0.485982745885849},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4757273495197296},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46984022855758667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4647386074066162},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42077648639678955},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41850242018699646},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.37944552302360535},{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.34769195318222046},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.2780434787273407},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.09094661474227905}],"concepts":[{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.8739058375358582},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8177935481071472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6701008081436157},{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.6373500227928162},{"id":"https://openalex.org/C69216139","wikidata":"https://www.wikidata.org/wiki/Q931783","display_name":"JPEG 2000","level":5,"score":0.485982745885849},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4757273495197296},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46984022855758667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4647386074066162},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42077648639678955},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41850242018699646},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.37944552302360535},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.34769195318222046},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.2780434787273407},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.09094661474227905},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tifs.2017.2779446","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2017.2779446","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1611.03233","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1611.03233","pdf_url":"https://arxiv.org/pdf/1611.03233","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1611.03233","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1611.03233","pdf_url":"https://arxiv.org/pdf/1611.03233","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2281262317","display_name":null,"funder_award_id":"61572329","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4553414329","display_name":null,"funder_award_id":"61402295","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6288753258","display_name":null,"funder_award_id":"61702340","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7251903255","display_name":null,"funder_award_id":"61772349","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W22271197","https://openalex.org/W1604614341","https://openalex.org/W1663899164","https://openalex.org/W1836465849","https://openalex.org/W1955882805","https://openalex.org/W1965064373","https://openalex.org/W1973466159","https://openalex.org/W1976570511","https://openalex.org/W2009130368","https://openalex.org/W2015721798","https://openalex.org/W2045110448","https://openalex.org/W2046180645","https://openalex.org/W2055625960","https://openalex.org/W2059019537","https://openalex.org/W2076063813","https://openalex.org/W2081564928","https://openalex.org/W2096156898","https://openalex.org/W2097117768","https://openalex.org/W2104705565","https://openalex.org/W2123849779","https://openalex.org/W2124664712","https://openalex.org/W2139842737","https://openalex.org/W2170598445","https://openalex.org/W2192227561","https://openalex.org/W2277839806","https://openalex.org/W2322622188","https://openalex.org/W2339370745","https://openalex.org/W2412509443","https://openalex.org/W2416075718","https://openalex.org/W2514127746","https://openalex.org/W2538511122","https://openalex.org/W2543123829","https://openalex.org/W2571906406","https://openalex.org/W2610979719","https://openalex.org/W2735904389","https://openalex.org/W2888845754","https://openalex.org/W2949117887","https://openalex.org/W2950094539","https://openalex.org/W2951787955","https://openalex.org/W2963682422","https://openalex.org/W2972355823","https://openalex.org/W4301488149","https://openalex.org/W6661850309","https://openalex.org/W6662048488"],"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/W1529294424","https://openalex.org/W2241212938","https://openalex.org/W2160587766","https://openalex.org/W2357125417"],"abstract_inverted_index":{"Adoption":[0],"of":[1,57,96,104,154,205],"deep":[2,71],"learning":[3,103],"in":[4,9,73,80,130,208],"image":[5],"steganalysis":[6,25],"is":[7,44,64,109,176],"still":[8],"its":[10],"initial":[11],"stage.":[12],"In":[13],"this":[14],"paper,":[15],"we":[16,171],"propose":[17],"a":[18,65,118,167,192,198],"generic":[19],"hybrid":[20],"deep-learning":[21,159],"framework":[22,36,175],"for":[23],"JPEG":[24,179],"incorporating":[26],"the":[27,48,52,58,75,81,94,101,105,152,163,184],"domain":[28],"knowledge":[29],"behind":[30],"rich":[31,59],"steganalytic":[32],"models.":[33,60],"Our":[34,148],"proposed":[35],"involves":[37],"two":[38],"main":[39],"stages.":[40],"The":[41,61,125],"first":[42],"stage":[43,63],"hand-crafted,":[45],"corresponding":[46],"to":[47,91,178,191],"convolution":[49,107],"phase":[50,56],"and":[51,54,88,156,183,196],"quantization":[53,155],"truncation":[55,157],"second":[62],"compound":[66],"deep-neural":[67],"network":[68],"containing":[69],"multiple":[70],"subnets,":[72],"which":[74],"model":[76,186],"parameters":[77],"are":[78,204],"learned":[79,185],"training":[82],"procedure.":[83],"We":[84,112],"provided":[85],"experimental":[86],"evidence":[87],"theoretical":[89],"reflections":[90],"argue":[92],"that":[93,151,173],"introduction":[95],"threshold":[97],"quantizers,":[98],"though":[99],"disabling":[100],"gradient-descent-based":[102],"bottom":[106],"phase,":[108],"indeed":[110],"cost-effective.":[111],"have":[113],"conducted":[114],"extensive":[115],"experiments":[116,132,149],"on":[117],"large-scale":[119],"data":[120,127,141,200],"set":[121,128,142],"extracted":[122],"from":[123],"ImageNet.":[124],"primary":[126],"used":[129],"our":[131,139,174],"contains":[133,143],"500":[134],"000":[135],"cover":[136,146],"images,":[137],"while":[138],"largest":[140],"five":[144],"million":[145],"images.":[147],"show":[150],"integration":[153],"into":[158],"steganalyzers":[160],"do":[161],"boost":[162],"detection":[164],"performance":[165],"by":[166],"clear":[168],"margin.":[169],"Furthermore,":[170],"demonstrate":[172],"insensitive":[177],"blocking":[180],"artifact":[181],"alterations,":[182],"can":[187],"be":[188],"easily":[189],"transferred":[190],"different":[193,199],"attacking":[194],"target":[195],"even":[197],"set.":[201],"These":[202],"properties":[203],"critical":[206],"importance":[207],"practical":[209],"applications.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":25},{"year":2020,"cited_by_count":41},{"year":2019,"cited_by_count":43},{"year":2018,"cited_by_count":22},{"year":2017,"cited_by_count":9}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2017-01-06T00:00:00"}