{"id":"https://openalex.org/W4406266295","doi":"https://doi.org/10.1109/gcce62371.2024.10760752","title":"Multimodal Adversarial Defense Trained on Features Extracted from Images and Brain Activity","display_name":"Multimodal Adversarial Defense Trained on Features Extracted from Images and Brain Activity","publication_year":2024,"publication_date":"2024-10-29","ids":{"openalex":"https://openalex.org/W4406266295","doi":"https://doi.org/10.1109/gcce62371.2024.10760752"},"language":"en","primary_location":{"id":"doi:10.1109/gcce62371.2024.10760752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce62371.2024.10760752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 13th Global Conference on Consumer Electronics (GCCE)","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/A5009137307","display_name":"Tasuku Nakajima","orcid":"https://orcid.org/0000-0002-2235-3478"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tasuku Nakajima","raw_affiliation_strings":["Hokkaido University,Sapporo, Hokkaido,Japan,060-0814"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hokkaido University,Sapporo, Hokkaido,Japan,060-0814","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033215072","display_name":"Keisuke Maeda","orcid":"https://orcid.org/0000-0001-8039-3462"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keisuke Maeda","raw_affiliation_strings":["Hokkaido University,Sapporo, Hokkaido,Japan,060-0814"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hokkaido University,Sapporo, Hokkaido,Japan,060-0814","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002757875","display_name":"Ren Togo","orcid":"https://orcid.org/0000-0002-4474-3995"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ren Togo","raw_affiliation_strings":["Hokkaido University,Sapporo, Hokkaido,Japan,060-0814"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hokkaido University,Sapporo, Hokkaido,Japan,060-0814","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009032240","display_name":"Takahiro Ogawa","orcid":"https://orcid.org/0000-0001-5332-8112"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Ogawa","raw_affiliation_strings":["Hokkaido University,Sapporo, Hokkaido,Japan,060-0814"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hokkaido University,Sapporo, Hokkaido,Japan,060-0814","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"last","author":{"id":null,"display_name":"Miki Haseyama","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Miki Haseyama","raw_affiliation_strings":["Hokkaido University,Sapporo, Hokkaido,Japan,060-0814"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hokkaido University,Sapporo, Hokkaido,Japan,060-0814","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205349734"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1183","last_page":"1184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9753000140190125,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9753000140190125,"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"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9559999704360962,"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/adversarial-system","display_name":"Adversarial system","score":0.8796937465667725},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6931756734848022},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6009314060211182},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3712461590766907}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8796937465667725},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6931756734848022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6009314060211182},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3712461590766907}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce62371.2024.10760752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce62371.2024.10760752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 13th Global Conference on Consumer Electronics (GCCE)","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":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs)":[3],"have":[4],"achieved":[5],"significant":[6],"advancements":[7],"in":[8],"artificial":[9],"intelligence":[10],"(AI)":[11],"but":[12],"remain":[13],"vulnerable":[14],"to":[15,50,74,96,109],"adversarial":[16,42,93],"attacks.":[17,35],"In":[18],"contrast,":[19],"the":[20,52,83,102],"human":[21],"cognitive":[22],"system,":[23],"integrating":[24],"multimodal":[25,41],"processing":[26],"and":[27,68],"brain":[28,47,106],"activity,":[29],"shows":[30],"high":[31],"robustness":[32,91],"against":[33,92],"such":[34],"This":[36,99],"paper":[37],"introduces":[38],"a":[39,76],"novel":[40],"defense":[43],"method":[44,89],"that":[45,87],"incorporates":[46],"activity":[48,107],"data":[49,62,73,108],"enhance":[51],"DNN":[53],"robustness.":[54],"We":[55],"use":[56],"functional":[57],"magnetic":[58],"resonance":[59],"imaging":[60],"(fMRI)":[61],"recorded":[63],"while":[64],"subjects":[65],"view":[66],"images":[67],"combine":[69],"it":[70],"with":[71],"visual":[72],"create":[75],"more":[77,111],"robust":[78,112],"classifier.":[79],"Experimental":[80],"results":[81],"using":[82],"NSD":[84],"dataset":[85],"demonstrate":[86],"our":[88],"improves":[90],"attacks":[94],"compared":[95],"traditional":[97],"methods.":[98],"research":[100],"underscores":[101],"potential":[103],"of":[104],"leveraging":[105],"develop":[110],"AI":[113],"systems.":[114]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
