{"id":"https://openalex.org/W4416251190","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229029","title":"Frequency maps reveal the correlation between Adversarial Attacks and Implicit Bias","display_name":"Frequency maps reveal the correlation between Adversarial Attacks and Implicit Bias","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251190","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229029"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5109609290","display_name":"Lorenzo Basile","orcid":null},"institutions":[{"id":"https://openalex.org/I142444530","display_name":"University of Trieste","ror":"https://ror.org/02n742c10","country_code":"IT","type":"education","lineage":["https://openalex.org/I142444530"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Lorenzo Basile","raw_affiliation_strings":["University of Trieste,Italy"],"affiliations":[{"raw_affiliation_string":"University of Trieste,Italy","institution_ids":["https://openalex.org/I142444530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054803959","display_name":"Nikos Karantzas","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikos Karantzas","raw_affiliation_strings":["Stanford University,USA"],"affiliations":[{"raw_affiliation_string":"Stanford University,USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074676799","display_name":"Alberto d\u2019Onofrio","orcid":"https://orcid.org/0000-0002-2190-272X"},"institutions":[{"id":"https://openalex.org/I142444530","display_name":"University of Trieste","ror":"https://ror.org/02n742c10","country_code":"IT","type":"education","lineage":["https://openalex.org/I142444530"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alberto D\u2019Onofrio","raw_affiliation_strings":["University of Trieste,Italy"],"affiliations":[{"raw_affiliation_string":"University of Trieste,Italy","institution_ids":["https://openalex.org/I142444530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064452080","display_name":"Luca Manzoni","orcid":"https://orcid.org/0000-0001-6312-7728"},"institutions":[{"id":"https://openalex.org/I142444530","display_name":"University of Trieste","ror":"https://ror.org/02n742c10","country_code":"IT","type":"education","lineage":["https://openalex.org/I142444530"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Manzoni","raw_affiliation_strings":["University of Trieste,Italy"],"affiliations":[{"raw_affiliation_string":"University of Trieste,Italy","institution_ids":["https://openalex.org/I142444530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060744592","display_name":"Luca Bortolussi","orcid":"https://orcid.org/0000-0001-8874-4001"},"institutions":[{"id":"https://openalex.org/I142444530","display_name":"University of Trieste","ror":"https://ror.org/02n742c10","country_code":"IT","type":"education","lineage":["https://openalex.org/I142444530"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Bortolussi","raw_affiliation_strings":["University of Trieste,Italy"],"affiliations":[{"raw_affiliation_string":"University of Trieste,Italy","institution_ids":["https://openalex.org/I142444530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085390890","display_name":"\u00c1lex Rodr\u00edguez","orcid":"https://orcid.org/0000-0002-0213-6695"},"institutions":[{"id":"https://openalex.org/I142444530","display_name":"University of Trieste","ror":"https://ror.org/02n742c10","country_code":"IT","type":"education","lineage":["https://openalex.org/I142444530"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alex Rodriguez","raw_affiliation_strings":["University of Trieste,Italy"],"affiliations":[{"raw_affiliation_string":"University of Trieste,Italy","institution_ids":["https://openalex.org/I142444530"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079466450","display_name":"Fabio Anselmi","orcid":"https://orcid.org/0000-0002-0264-4761"},"institutions":[{"id":"https://openalex.org/I142444530","display_name":"University of Trieste","ror":"https://ror.org/02n742c10","country_code":"IT","type":"education","lineage":["https://openalex.org/I142444530"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabio Anselmi","raw_affiliation_strings":["University of Trieste,Italy"],"affiliations":[{"raw_affiliation_string":"University of Trieste,Italy","institution_ids":["https://openalex.org/I142444530"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5109609290"],"corresponding_institution_ids":["https://openalex.org/I142444530"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19453847,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9947999715805054,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9947999715805054,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.0008999999845400453,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.000699999975040555,"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":0.8841999769210815},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5054000020027161},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47749999165534973},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.44690001010894775},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4189999997615814},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4162999987602234}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8841999769210815},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6079000234603882},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5116000175476074},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5054000020027161},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47749999165534973},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.44690001010894775},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4189999997615814},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4162999987602234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38339999318122864},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38179999589920044},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.35280001163482666},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3506999909877777},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.3228999972343445},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30649998784065247},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.2800000011920929},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":22,"referenced_works":["https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2243397390","https://openalex.org/W2890304135","https://openalex.org/W2963857521","https://openalex.org/W2964047251","https://openalex.org/W2964082701","https://openalex.org/W2965496811","https://openalex.org/W3034175346","https://openalex.org/W3088909400","https://openalex.org/W3094502228","https://openalex.org/W3094984771","https://openalex.org/W3191617243","https://openalex.org/W3198796775","https://openalex.org/W3201579356","https://openalex.org/W4225928697","https://openalex.org/W4237723258","https://openalex.org/W4280545399","https://openalex.org/W4285033916","https://openalex.org/W4293846201","https://openalex.org/W4377941395","https://openalex.org/W4399868320"],"related_works":[],"abstract_inverted_index":{"Despite":[0],"their":[1],"impressive":[2],"performance":[3],"in":[4,100,168],"classification":[5,88],"tasks,":[6],"neural":[7,43],"networks":[8,44],"are":[9,178],"known":[10],"to":[11,14,24,109],"be":[12],"vulnerable":[13],"adversarial":[15,77,137,176,187],"attacks,":[16],"subtle":[17],"perturbations":[18,37],"of":[19,42,56,64,73,89,123,152,175],"the":[20,26,33,39,57,62,65,81,95,113,125,132,165,172],"input":[21],"data":[22],"designed":[23],"deceive":[25],"model.":[27],"In":[28],"this":[29,50,140],"work,":[30],"we":[31,52,69,145],"investigate":[32],"correlation":[34,114],"between":[35,115,156],"these":[36,116],"and":[38,76,111,171,181],"implicit":[40,59,74],"bias":[41,60,75,167],"trained":[45],"with":[46,131],"gradient-based":[47],"algorithms.":[48],"To":[49,139],"end,":[51,141],"analyse":[53,112],"a":[54,120,147],"representation":[55],"network\u2019s":[58,126],"through":[61],"lens":[63],"Fourier":[66,169],"transform.":[67],"Specifically,":[68],"identify":[70],"unique":[71],"fingerprints":[72],"attacks":[78,177],"by":[79,136],"calculating":[80],"minimal,":[82],"essential":[83,117],"frequencies":[84,96,174],"needed":[85],"for":[86,186],"accurate":[87],"each":[90],"image,":[91],"as":[92,94],"well":[93],"that":[97,164],"drive":[98],"misclassification":[99],"its":[101],"adversarially":[102],"perturbed":[103],"counterpart.":[104],"This":[105],"approach":[106],"enables":[107],"us":[108],"uncover":[110],"frequencies,":[118],"providing":[119],"precise":[121],"map":[122],"how":[124],"biases":[127],"align":[128],"or":[129],"contrast":[130],"frequency":[133],"components":[134],"exploited":[135],"attacks.":[138],"among":[142],"other":[143],"methods,":[144],"use":[146],"newly":[148],"introduced":[149],"technique":[150],"capable":[151],"detecting":[153],"nonlinear":[154],"correlations":[155],"high-dimensional":[157],"datasets.":[158],"Our":[159],"results":[160],"provide":[161],"empirical":[162],"evidence":[163],"network":[166],"space":[170],"target":[173],"highly":[179],"correlated":[180],"suggest":[182],"new":[183],"potential":[184],"strategies":[185],"defence.":[188],"Code":[189],"is":[190],"available":[191],"at":[192],"https://github.com/lorenzobasile/ImplicitBiasAdversarial":[193]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}