{"id":"https://openalex.org/W4402980335","doi":"https://doi.org/10.1109/icme57554.2024.10688355","title":"Fragile Model Watermark for integrity protection: leveraging boundary volatility and sensitive sample-pairing","display_name":"Fragile Model Watermark for integrity protection: leveraging boundary volatility and sensitive sample-pairing","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402980335","doi":"https://doi.org/10.1109/icme57554.2024.10688355"},"language":"en","primary_location":{"id":"doi:10.1109/icme57554.2024.10688355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10688355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","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/A5101237433","display_name":"Zhenzhe Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"ZhenZhe Gao","raw_affiliation_strings":["East China Normal University,Shanghai Key Laboratory of Multidimensional Information Processing,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"East China Normal University,Shanghai Key Laboratory of Multidimensional Information Processing,Shanghai,China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087798028","display_name":"Zhenjun Tang","orcid":"https://orcid.org/0000-0003-3664-1363"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenjun Tang","raw_affiliation_strings":["Guangxi Normal University,Guangxi Key Lab of Multi-Source Information Mining & Security,Guilin,China"],"affiliations":[{"raw_affiliation_string":"Guangxi Normal University,Guangxi Key Lab of Multi-Source Information Mining & Security,Guilin,China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035489942","display_name":"Zhaoxia Yin","orcid":"https://orcid.org/0000-0003-0387-4806"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoxia Yin","raw_affiliation_strings":["East China Normal University,Shanghai Key Laboratory of Multidimensional Information Processing,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"East China Normal University,Shanghai Key Laboratory of Multidimensional Information Processing,Shanghai,China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068027800","display_name":"Baoyuan Wu","orcid":"https://orcid.org/0000-0003-2183-5990"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoyuan Wu","raw_affiliation_strings":["The Chinese University of Hong Kong,Shenzhen Research Institute of Big Data,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Shenzhen Research Institute of Big Data,Shenzhen,China","institution_ids":["https://openalex.org/I4210116924","https://openalex.org/I4210099586"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101615349","display_name":"Yue Lu","orcid":"https://orcid.org/0000-0002-8784-4657"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Lu","raw_affiliation_strings":["East China Normal University,Shanghai Key Laboratory of Multidimensional Information Processing,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"East China Normal University,Shanghai Key Laboratory of Multidimensional Information Processing,Shanghai,China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101237433"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.5248,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66289308,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9908999800682068,"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":0.9908999800682068,"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/T13999","display_name":"Digital Rights Management and Security","score":0.9570000171661377,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/pairing","display_name":"Pairing","score":0.717330813407898},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.591545820236206},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5234676599502563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5011286735534668},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4732834994792938},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.4719369113445282},{"id":"https://openalex.org/keywords/digital-watermarking","display_name":"Digital watermarking","score":0.43900761008262634},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.20612424612045288},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1138228178024292},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.09794840216636658},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08472627401351929},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08194467425346375},{"id":"https://openalex.org/keywords/condensed-matter-physics","display_name":"Condensed matter physics","score":0.07754036784172058}],"concepts":[{"id":"https://openalex.org/C14103023","wikidata":"https://www.wikidata.org/wiki/Q11681459","display_name":"Pairing","level":3,"score":0.717330813407898},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.591545820236206},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5234676599502563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5011286735534668},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4732834994792938},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.4719369113445282},{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.43900761008262634},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.20612424612045288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1138228178024292},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.09794840216636658},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08472627401351929},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08194467425346375},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.07754036784172058},{"id":"https://openalex.org/C54101563","wikidata":"https://www.wikidata.org/wiki/Q124131","display_name":"Superconductivity","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme57554.2024.10688355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10688355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"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":10,"referenced_works":["https://openalex.org/W2294710185","https://openalex.org/W2948833786","https://openalex.org/W3041840141","https://openalex.org/W3214052054","https://openalex.org/W4383896823","https://openalex.org/W4386160509","https://openalex.org/W4389794056","https://openalex.org/W4389951825","https://openalex.org/W4392239625","https://openalex.org/W6682889407"],"related_works":["https://openalex.org/W2137394636","https://openalex.org/W2358993821","https://openalex.org/W1516446231","https://openalex.org/W2098152888","https://openalex.org/W1559740347","https://openalex.org/W2040356834","https://openalex.org/W2080353903","https://openalex.org/W2385289568","https://openalex.org/W2381486749","https://openalex.org/W1514507288"],"abstract_inverted_index":{"Neural":[0],"networks":[1,13],"have":[2],"increasingly":[3],"influenced":[4],"people\u2019s":[5],"lives.":[6],"Ensuring":[7],"the":[8,58,64,93,107,120,127,140,151],"faithful":[9],"deployment":[10],"of":[11,60,98,111,126,146],"neural":[12],"as":[14,22,34,66,68,115,117],"designed":[15],"by":[16],"their":[17,83],"model":[18,40,65,94],"owners":[19],"is":[20],"crucial,":[21],"they":[23],"may":[24],"be":[25],"susceptible":[26],"to":[27,43,52,150],"various":[28],"malicious":[29],"or":[30],"unintentional":[31],"modifications,":[32],"such":[33],"backdooring":[35],"and":[36,79,119,137,143],"poisoning":[37],"attacks.":[38],"Fragile":[39],"watermarks":[41],"aim":[42],"prevent":[44],"unexpected":[45],"tampering":[46,62],"that":[47,106],"could":[48],"lead":[49],"DNN":[50],"models":[51,136],"make":[53],"incorrect":[54],"decisions.":[55],"They":[56],"ensure":[57],"detection":[59],"any":[61],"with":[63],"sensitively":[67],"possible.":[69],"However,":[70],"prior":[71],"watermarking":[72],"methods":[73],"suffered":[74],"from":[75],"inefficient":[76],"sample":[77],"generation":[78,144],"insufficient":[80],"sensitivity,":[81],"limiting":[82],"practical":[84],"applicability.":[85],"Our":[86],"approach":[87],"employs":[88],"a":[89],"sample-pairing":[90],"technique,":[91],"placing":[92],"boundaries":[95],"between":[96],"pairs":[97],"samples,":[99],"while":[100],"simultaneously":[101],"maximizing":[102],"logits.":[103],"This":[104],"ensures":[105],"model\u2019s":[108],"decision":[109],"results":[110],"sensitive":[112],"samples":[113],"change":[114],"much":[116],"possible":[118],"Top-1":[121],"labels":[122],"easily":[123],"alter":[124],"regardless":[125],"direction":[128],"it":[129],"moves.":[130],"Experimental":[131],"evaluations":[132],"conducted":[133],"across":[134],"multiple":[135],"datasets":[138],"demonstrate":[139],"superior":[141],"sensitivity":[142],"efficiency":[145],"our":[147],"method":[148],"compared":[149],"current":[152],"approaches.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2024-10-01T00:00:00"}