{"id":"https://openalex.org/W3177518343","doi":"https://doi.org/10.1142/s1793351x21400043","title":"A Countermeasure Method Using Poisonous Data Against Poisoning Attacks on IoT Machine Learning","display_name":"A Countermeasure Method Using Poisonous Data Against Poisoning Attacks on IoT Machine Learning","publication_year":2021,"publication_date":"2021-06-01","ids":{"openalex":"https://openalex.org/W3177518343","doi":"https://doi.org/10.1142/s1793351x21400043","mag":"3177518343"},"language":"en","primary_location":{"id":"doi:10.1142/s1793351x21400043","is_oa":true,"landing_page_url":"https://doi.org/10.1142/s1793351x21400043","pdf_url":null,"source":{"id":"https://openalex.org/S4210201727","display_name":"International Journal of Semantic Computing","issn_l":"1793-351X","issn":["1793-351X","1793-7108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Semantic Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1142/s1793351x21400043","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054017495","display_name":"Tomoki Chiba","orcid":null},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tomoki Chiba","raw_affiliation_strings":["Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045716284","display_name":"Yuichi Sei","orcid":"https://orcid.org/0000-0002-2552-6717"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuichi Sei","raw_affiliation_strings":["Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013743040","display_name":"Yasuyuki Tahara","orcid":"https://orcid.org/0000-0002-1939-4455"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasuyuki Tahara","raw_affiliation_strings":["Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013259601","display_name":"Akihiko Ohsuga","orcid":"https://orcid.org/0000-0001-6717-7028"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akihiko Ohsuga","raw_affiliation_strings":["Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan","institution_ids":["https://openalex.org/I20529979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054017495"],"corresponding_institution_ids":["https://openalex.org/I20529979"],"apc_list":null,"apc_paid":null,"fwci":0.9794,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.80587446,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"15","issue":"02","first_page":"215","last_page":"240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994000196456909,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/machine-learning","display_name":"Machine learning","score":0.8110403418540955},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7744216918945312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7241831421852112},{"id":"https://openalex.org/keywords/countermeasure","display_name":"Countermeasure","score":0.4255252778530121},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.41199684143066406}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.8110403418540955},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7744216918945312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7241831421852112},{"id":"https://openalex.org/C21593369","wikidata":"https://www.wikidata.org/wiki/Q1032176","display_name":"Countermeasure","level":2,"score":0.4255252778530121},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.41199684143066406},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s1793351x21400043","is_oa":true,"landing_page_url":"https://doi.org/10.1142/s1793351x21400043","pdf_url":null,"source":{"id":"https://openalex.org/S4210201727","display_name":"International Journal of Semantic Computing","issn_l":"1793-351X","issn":["1793-351X","1793-7108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Semantic Computing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1142/s1793351x21400043","is_oa":true,"landing_page_url":"https://doi.org/10.1142/s1793351x21400043","pdf_url":null,"source":{"id":"https://openalex.org/S4210201727","display_name":"International Journal of Semantic Computing","issn_l":"1793-351X","issn":["1793-351X","1793-7108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Semantic Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W9657784","https://openalex.org/W1988277750","https://openalex.org/W2095577883","https://openalex.org/W2125908420","https://openalex.org/W2146211964","https://openalex.org/W2151298633","https://openalex.org/W2157535873","https://openalex.org/W2162552722","https://openalex.org/W2342408547","https://openalex.org/W2475730566","https://openalex.org/W2535690855","https://openalex.org/W2612690371","https://openalex.org/W2762644836","https://openalex.org/W2766705682","https://openalex.org/W2892908011","https://openalex.org/W2893554781","https://openalex.org/W2949506549","https://openalex.org/W2962763344","https://openalex.org/W2963343288","https://openalex.org/W2963844355","https://openalex.org/W2964153729","https://openalex.org/W2964253222","https://openalex.org/W2967540978","https://openalex.org/W2981446616","https://openalex.org/W2983044655","https://openalex.org/W2985913519","https://openalex.org/W2990138404","https://openalex.org/W2997357271","https://openalex.org/W3026477862","https://openalex.org/W3048339221","https://openalex.org/W3099185017","https://openalex.org/W3130178478","https://openalex.org/W3130279822","https://openalex.org/W4247200422"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W2350438938","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"In":[0,70],"the":[1,13,41,43,47,92,98,102,117,121,148,151,182,202,216,219,229,232,236,249,261,270,286,295,308,314,318,325,328,338,351,356,362,369,375,386,389],"modern":[2],"world,":[3],"several":[4],"areas":[5],"of":[6,15,21,65,73,88,94,111,150,164,184,204,211,218,231,235,238,251,269,276,297,327,341,350,358,371,388],"our":[7,298],"lives":[8],"can":[9,127,255],"be":[10,61,79,105,176,291],"improved,":[11],"in":[12,19,63,81,137,147,157,173,193,209,253,305,324,345,347,366],"form":[14],"diverse":[16],"additional":[17],"dimensions,":[18],"terms":[20,64,210],"quality,":[22],"by":[23,361,382],"machine":[24,28,50,68,75,144,159,220],"learning.":[25,69],"When":[26],"building":[27],"learning":[29,51,76,145,160,221],"models,":[30],"open":[31],"data":[32,96,100,165,206,240,252,263,279,288,353],"are":[33,53,354],"often":[34],"used.":[35],"Although":[36],"this":[37,71,89,138,282,334],"trend":[38],"is":[39,135,198,225,364],"on":[40,49,228,260,281],"rise,":[42],"monetary":[44],"losses":[45],"since":[46],"attacks":[48,192],"models":[52,77,103,146,161],"also":[54,226],"rising.":[55],"Preparation":[56],"is,":[57],"thus,":[58],"believed":[59],"to":[60,104,119,124,129,190,214,247,312,316,368],"indispensable":[62],"embarking":[66],"upon":[67],"field":[72],"endeavor,":[74],"may":[78],"compromised":[80],"various":[82],"ways,":[83],"including":[84],"poisoning":[85,152,191],"attacks.":[86],"Assaults":[87],"nature":[90],"involve":[91],"incorporation":[93],"injurious":[95],"into":[97],"training":[99,179,352],"rendering":[101],"substantively":[106],"less":[107],"accurate.":[108],"The":[109,171,245,274,378],"circumstances":[110,346],"every":[112],"individual":[113],"case":[114],"will":[115,175,186,289],"determine":[116],"degree":[118,315,357],"which":[120,158,248,317,348],"impairment":[122],"due":[123],"such":[125,194,277],"intrusions":[126],"lead":[128],"extensive":[130],"disruption.":[131],"A":[132],"modus":[133],"operandi":[134],"proffered":[136],"research":[139],"as":[140,178,241],"a":[141,155,188],"safeguard":[142],"for":[143],"face":[149],"menace,":[153],"envisaging":[154],"milieu":[156],"make":[162],"use":[163,237],"that":[166,285,336],"emanate":[167],"from":[168,242],"numerous":[169],"sources.":[170],"information":[172],"question":[174,254],"presented":[177],"data,":[180],"and":[181],"diversity":[183],"sources":[185,271],"constitute":[187],"barrier":[189],"circumstances.":[195],"Every":[196],"source":[197],"evaluated":[199,303],"separately,":[200],"with":[201,267,307],"weight":[203],"each":[205,243,268],"component":[207],"assessed":[208],"its":[212],"ability":[213],"affect":[215],"precision":[217,359],"model.":[222],"An":[223],"appraisal":[224,342],"conducted":[227],"basis":[230],"theoretical":[233],"effect":[234],"corrupt":[239],"source.":[244],"extent":[246],"subgroup":[250],"undermine":[256],"overall":[257],"accuracy":[258],"depends":[259],"estimated":[262],"removal":[264],"rate":[265],"associated":[266],"described":[272],"above.":[273],"exclusion":[275],"isolated":[278],"based":[280],"figure":[283,370],"ensures":[284],"standard":[287,310],"not":[290],"tainted.":[292],"To":[293],"evaluate":[294],"efficacy":[296],"suggested":[299,381],"preventive":[300],"measure,":[301],"we":[302],"it":[304],"comparison":[306],"well-known":[309],"techniques":[311],"assess":[313],"model":[319,363,390],"was":[320,331,343],"providing":[321],"accurate":[322],"conclusions":[323],"wake":[326],"change.":[329],"It":[330],"demonstrated":[332],"during":[333],"test":[335],"when":[337],"innovative":[339],"mode":[340],"applied,":[344],"17%":[349],"corrupt,":[355],"offered":[360],"89%,":[365],"contrast":[367],"83%":[372],"acquired":[373],"through":[374],"traditional":[376],"technique.":[377],"corrective":[379],"technique":[380],"us":[383],"thus":[384],"boosted":[385],"resilience":[387],"against":[391],"harmful":[392],"intrusion.":[393]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}