{"id":"https://openalex.org/W4388517698","doi":"https://doi.org/10.1109/fuzz52849.2023.10309766","title":"NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks","display_name":"NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks","publication_year":2023,"publication_date":"2023-08-13","ids":{"openalex":"https://openalex.org/W4388517698","doi":"https://doi.org/10.1109/fuzz52849.2023.10309766"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz52849.2023.10309766","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz52849.2023.10309766","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Fuzzy Systems (FUZZ)","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/A5035335021","display_name":"Wenkai Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I84475105","display_name":"Embry\u2013Riddle Aeronautical University","ror":"https://ror.org/010jskt71","country_code":"US","type":"education","lineage":["https://openalex.org/I84475105"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wenkai Tan","raw_affiliation_strings":["Embry-Riddle Aeronautical University,FL,USA,32114"],"affiliations":[{"raw_affiliation_string":"Embry-Riddle Aeronautical University,FL,USA,32114","institution_ids":["https://openalex.org/I84475105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008202991","display_name":"Justus Renkhoff","orcid":"https://orcid.org/0000-0002-7021-734X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Justus Renkhoff","raw_affiliation_strings":["University of Maryland,MD,USA,21250"],"affiliations":[{"raw_affiliation_string":"University of Maryland,MD,USA,21250","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067109059","display_name":"Alvaro Velasquez","orcid":"https://orcid.org/0000-0001-6757-105X"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alvaro Velasquez","raw_affiliation_strings":["University of Colorado Boulder,CO,USA,80309"],"affiliations":[{"raw_affiliation_string":"University of Colorado Boulder,CO,USA,80309","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100420915","display_name":"Ziyu Wang","orcid":"https://orcid.org/0000-0002-2844-395X"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziyu Wang","raw_affiliation_strings":["Old Dominion University,VA,USA,23529"],"affiliations":[{"raw_affiliation_string":"Old Dominion University,VA,USA,23529","institution_ids":["https://openalex.org/I81365321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006167598","display_name":"Lusi Li","orcid":"https://orcid.org/0000-0002-4323-2632"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lusi Li","raw_affiliation_strings":["Old Dominion University,VA,USA,23529"],"affiliations":[{"raw_affiliation_string":"Old Dominion University,VA,USA,23529","institution_ids":["https://openalex.org/I81365321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100370341","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0001-6043-6971"},"institutions":[{"id":"https://openalex.org/I109963312","display_name":"University of Tennessee at Martin","ror":"https://ror.org/01244fm76","country_code":"US","type":"education","lineage":["https://openalex.org/I109963312"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["University of Tennessee at Martin,TN,USA,38237"],"affiliations":[{"raw_affiliation_string":"University of Tennessee at Martin,TN,USA,38237","institution_ids":["https://openalex.org/I109963312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028748926","display_name":"Shuteng Niu","orcid":"https://orcid.org/0000-0002-1069-9236"},"institutions":[{"id":"https://openalex.org/I157417397","display_name":"Bowling Green State University","ror":"https://ror.org/00ay7va13","country_code":"US","type":"education","lineage":["https://openalex.org/I157417397"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuteng Niu","raw_affiliation_strings":["Bowling Green State University,OH,USA,43403"],"affiliations":[{"raw_affiliation_string":"Bowling Green State University,OH,USA,43403","institution_ids":["https://openalex.org/I157417397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346602","display_name":"Fan Yang","orcid":"https://orcid.org/0000-0002-0378-060X"},"institutions":[{"id":"https://openalex.org/I84475105","display_name":"Embry\u2013Riddle Aeronautical University","ror":"https://ror.org/010jskt71","country_code":"US","type":"education","lineage":["https://openalex.org/I84475105"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fan Yang","raw_affiliation_strings":["Embry-Riddle Aeronautical University,FL,USA,32114"],"affiliations":[{"raw_affiliation_string":"Embry-Riddle Aeronautical University,FL,USA,32114","institution_ids":["https://openalex.org/I84475105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100765920","display_name":"Yongxin Liu","orcid":"https://orcid.org/0000-0003-4527-8623"},"institutions":[{"id":"https://openalex.org/I84475105","display_name":"Embry\u2013Riddle Aeronautical University","ror":"https://ror.org/010jskt71","country_code":"US","type":"education","lineage":["https://openalex.org/I84475105"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yongxin Liu","raw_affiliation_strings":["Embry-Riddle Aeronautical University,FL,USA,32114"],"affiliations":[{"raw_affiliation_string":"Embry-Riddle Aeronautical University,FL,USA,32114","institution_ids":["https://openalex.org/I84475105"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079301418","display_name":"Houbing Song","orcid":"https://orcid.org/0000-0003-2631-9223"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Houbing Song","raw_affiliation_strings":["University of Maryland,MD,USA,21250"],"affiliations":[{"raw_affiliation_string":"University of Maryland,MD,USA,21250","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5035335021"],"corresponding_institution_ids":["https://openalex.org/I84475105"],"apc_list":null,"apc_paid":null,"fwci":1.4011,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.85332138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"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":1.0,"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":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9934999942779541,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9747999906539917,"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/adversarial-system","display_name":"Adversarial system","score":0.9040895700454712},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7469302415847778},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6413442492485046},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6233358979225159},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.6074343919754028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5926026105880737},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5867316722869873},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5700515508651733},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4831816256046295},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4444279670715332},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.44121965765953064},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.4341749846935272},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37494826316833496},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3201913833618164},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.21462824940681458},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1018947958946228}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9040895700454712},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7469302415847778},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6413442492485046},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6233358979225159},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.6074343919754028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5926026105880737},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5867316722869873},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5700515508651733},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4831816256046295},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4444279670715332},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.44121965765953064},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.4341749846935272},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37494826316833496},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3201913833618164},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.21462824940681458},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1018947958946228},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz52849.2023.10309766","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz52849.2023.10309766","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Fuzzy Systems (FUZZ)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G5665895995","display_name":null,"funder_award_id":"2309760,2317117","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1883420340","https://openalex.org/W1945616565","https://openalex.org/W2108598243","https://openalex.org/W2117539524","https://openalex.org/W2510850936","https://openalex.org/W2516809705","https://openalex.org/W2616028256","https://openalex.org/W2740924709","https://openalex.org/W2751936342","https://openalex.org/W2765793020","https://openalex.org/W2890038638","https://openalex.org/W2949905295","https://openalex.org/W2951576642","https://openalex.org/W2957905354","https://openalex.org/W2962858109","https://openalex.org/W2962878175","https://openalex.org/W2964197269","https://openalex.org/W2971626200","https://openalex.org/W2987875759","https://openalex.org/W2994987245","https://openalex.org/W3007264885","https://openalex.org/W3021378896","https://openalex.org/W3040887543","https://openalex.org/W3081923410","https://openalex.org/W3120460133","https://openalex.org/W3124174388","https://openalex.org/W3127579051","https://openalex.org/W3175985367","https://openalex.org/W3176482836","https://openalex.org/W3217401178","https://openalex.org/W4221140307","https://openalex.org/W4226216828","https://openalex.org/W4287692845","https://openalex.org/W4304820450","https://openalex.org/W6637373629","https://openalex.org/W6639568328","https://openalex.org/W6640425456","https://openalex.org/W6748204703","https://openalex.org/W6750592626","https://openalex.org/W6754108890","https://openalex.org/W6763621065","https://openalex.org/W6763887731","https://openalex.org/W6781769330","https://openalex.org/W6788494687","https://openalex.org/W6804107042","https://openalex.org/W6810381944"],"related_works":["https://openalex.org/W2950183588","https://openalex.org/W3080754722","https://openalex.org/W4383221314","https://openalex.org/W3093978547","https://openalex.org/W2953536436","https://openalex.org/W3203790781","https://openalex.org/W4313346231","https://openalex.org/W2738001131","https://openalex.org/W4285785480","https://openalex.org/W2997056298"],"abstract_inverted_index":{"Deep":[0,4],"Learning":[1],"(DL)":[2],"and":[3,23,83,115,130,152,154],"Neural":[5],"Networks":[6],"(DNNs)":[7],"are":[8,30,61,78],"widely":[9],"used":[10,98],"in":[11,33,139,163],"various":[12],"domains.":[13],"However,":[14],"adversarial":[15,64,81,101,128,146,180],"attacks":[16,181],"can":[17,73,96],"easily":[18],"mislead":[19],"a":[20,106,171],"neural":[21,184],"network":[22,57],"lead":[24],"to":[25,49,80,99,127,134,174],"wrong":[26],"decisions.":[27],"Defense":[28],"mechanisms":[29],"highly":[31,125],"preferred":[32],"safety-":[34],"critical":[35],"applications.":[36],"In":[37,69],"this":[38],"paper,":[39],"firstly,":[40],"we":[41,104,143,155],"use":[42],"the":[43,51,55,90,140],"gradient":[44],"class":[45,119],"activation":[46,120],"map":[47],"(GradCAM)":[48],"analyze":[50],"behavior":[52,91,150,160],"deviation":[53,92,151,161],"of":[54,93,179],"VGG-16":[56],"when":[58],"its":[59,164],"inputs":[60],"mixed":[62,138],"with":[63],"perturbation":[65,82],"or":[66],"Gaussian":[67,84,135],"noise.":[68,85],"particular,":[70],"our":[71],"method":[72],"locate":[74],"vulnerable":[75,94],"layers":[76,95],"that":[77,89,110,157],"sensitive":[79,126],"We":[86],"also":[87],"show":[88,156],"be":[97],"detect":[100],"examples.":[102],"Secondly,":[103],"propose":[105],"novel":[107],"NoiseCAM":[108,158],"algorithm":[109,123],"integrates":[111],"information":[112],"from":[113],"globally":[114],"pixel-":[116],"level":[117],"weighted":[118],"maps.":[121],"Our":[122,167],"is":[124],"perturbations":[129],"will":[131],"not":[132],"respond":[133],"random":[136],"noise":[137],"inputs.":[141],"Third,":[142],"compare":[144],"detecting":[145],"examples":[147],"using":[148],"both":[149],"NoiseCAM,":[153],"outperforms":[159],"modeling":[162],"overall":[165],"performance.":[166],"work":[168],"could":[169],"provide":[170],"useful":[172],"tool":[173],"defend":[175],"against":[176],"certain":[177],"types":[178],"on":[182],"deep":[183],"networks.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
