{"id":"https://openalex.org/W7138402769","doi":"https://doi.org/10.1007/s10207-026-01225-1","title":"Mixed Perturbation: Generating Directionally Diverse Perturbations for Adversarial Training","display_name":"Mixed Perturbation: Generating Directionally Diverse Perturbations for Adversarial Training","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7138402769","doi":"https://doi.org/10.1007/s10207-026-01225-1"},"language":"en","primary_location":{"id":"doi:10.1007/s10207-026-01225-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10207-026-01225-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10207-026-01225-1.pdf","source":{"id":"https://openalex.org/S164062316","display_name":"International Journal of Information Security","issn_l":"1615-5262","issn":["1615-5262","1615-5270"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Security","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10207-026-01225-1.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107092658","display_name":"Changhun Hyun","orcid":"https://orcid.org/0000-0002-6984-2375"},"institutions":[{"id":"https://openalex.org/I199143407","display_name":"Sunchon National University","ror":"https://ror.org/043jqrs76","country_code":"KR","type":"education","lineage":["https://openalex.org/I199143407"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Changhun Hyun","raw_affiliation_strings":["Department of Computer Education, Sunchon National University, 255, Jungang-ro, Suncheon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Education, Sunchon National University, 255, Jungang-ro, Suncheon, Republic of Korea","institution_ids":["https://openalex.org/I199143407"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010610758","display_name":"Hyeyoung Park","orcid":"https://orcid.org/0000-0003-0716-4385"},"institutions":[{"id":"https://openalex.org/I163584902","display_name":"Daegu Health College","ror":"https://ror.org/00pffbm70","country_code":"KR","type":"education","lineage":["https://openalex.org/I163584902"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyeyoung Park","raw_affiliation_strings":["School of Computer Science and Engineering, 80, Daehak-ro, Buk-gu, Daegu, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, 80, Daehak-ro, Buk-gu, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I163584902"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5010610758"],"corresponding_institution_ids":["https://openalex.org/I163584902"],"apc_list":{"value":2590,"currency":"EUR","value_usd":3190},"apc_paid":{"value":2590,"currency":"EUR","value_usd":3190},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68456652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9959999918937683,"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":0.9959999918937683,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.0003000000142492354,"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":0.9424999952316284},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.5764999985694885},{"id":"https://openalex.org/keywords/random-noise","display_name":"Random noise","score":0.4415999948978424},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.3749000132083893},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.30959999561309814}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9424999952316284},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7387999892234802},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.5764999985694885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5444999933242798},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5072000026702881},{"id":"https://openalex.org/C2986577269","wikidata":"https://www.wikidata.org/wiki/Q11306265","display_name":"Random noise","level":2,"score":0.4415999948978424},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3749000132083893},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34940001368522644},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26669999957084656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10207-026-01225-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10207-026-01225-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10207-026-01225-1.pdf","source":{"id":"https://openalex.org/S164062316","display_name":"International Journal of Information Security","issn_l":"1615-5262","issn":["1615-5262","1615-5270"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Security","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10207-026-01225-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10207-026-01225-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10207-026-01225-1.pdf","source":{"id":"https://openalex.org/S164062316","display_name":"International Journal of Information Security","issn_l":"1615-5262","issn":["1615-5262","1615-5270"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Security","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G692463651","display_name":null,"funder_award_id":"BK21 FOUR project (AI-driven Convergence Software Education Research Program) (412020214871)","funder_id":"https://openalex.org/F4320321408","funder_display_name":"Ministry of Education"}],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138402769.pdf","grobid_xml":"https://content.openalex.org/works/W7138402769.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1614862348","https://openalex.org/W1932198206","https://openalex.org/W2067713319","https://openalex.org/W2112796928","https://openalex.org/W2603766943","https://openalex.org/W2913266441","https://openalex.org/W2924551358","https://openalex.org/W2962933288","https://openalex.org/W2963143631","https://openalex.org/W2963384482","https://openalex.org/W2963542245","https://openalex.org/W2963564844","https://openalex.org/W2963857521","https://openalex.org/W2963952467","https://openalex.org/W2964082701","https://openalex.org/W2964116600","https://openalex.org/W2996564870","https://openalex.org/W3021182036","https://openalex.org/W3095066959","https://openalex.org/W3105389675","https://openalex.org/W3109744225","https://openalex.org/W3122061855","https://openalex.org/W3137281193","https://openalex.org/W3159616439","https://openalex.org/W3194730353","https://openalex.org/W3211269067","https://openalex.org/W4288359148","https://openalex.org/W4288363831","https://openalex.org/W4288363925","https://openalex.org/W4312335729","https://openalex.org/W4312882434","https://openalex.org/W4313068277","https://openalex.org/W4319323349","https://openalex.org/W4328028668","https://openalex.org/W4385768289","https://openalex.org/W4386065469","https://openalex.org/W4387075729","https://openalex.org/W4391931465","https://openalex.org/W4394625762","https://openalex.org/W4394647257","https://openalex.org/W4403364603","https://openalex.org/W4404088298","https://openalex.org/W4405241549","https://openalex.org/W4405356597","https://openalex.org/W4406891937","https://openalex.org/W6948309317"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"The":[1,98],"adversarial":[2,21,42,58,68,93,96,143],"vulnerability":[3],"of":[4,16,36,41,52,127,141,203],"deep":[5],"learning":[6,66],"models":[7,55],"poses":[8],"a":[9,80,117,146,194],"significant":[10],"challenge":[11],"to":[12,62,90,184],"the":[13,31,37,50,73,108,124,128,139,157,168,173,200],"safe":[14],"commercialization":[15],"AI":[17],"technologies.":[18],"Although":[19],"numerous":[20],"defenses":[22],"have":[23],"been":[24],"proposed,":[25],"most":[26],"offer":[27],"limited":[28],"robustness,":[29],"emphasizing":[30],"need":[32],"for":[33,95,212],"continued":[34],"exploration":[35,64],"properties":[38],"and":[39,65,111,209],"causes":[40],"vulnerabilities.":[43],"In":[44,75,188],"this":[45,76],"study,":[46],"we":[47,78,198],"hypothesize":[48],"that":[49,70,156],"phenomenon":[51],"adversarially":[53],"trained":[54],"exhibiting":[56],"low":[57],"accuracies":[59],"is":[60],"due":[61],"insufficient":[63],"from":[67,106,145],"examples":[69,94,144],"exist":[71],"on":[72,151],"manifold.":[74],"regard,":[77],"propose":[79],"novel":[81],"perturbation":[82,86,131,136,179],"generation":[83],"method,":[84,197],"\u201cmixed":[85],"(MP),\u201d":[87],"which":[88],"aims":[89],"discover":[91],"various":[92],"training.":[97],"proposed":[99],"method":[100],"generates":[101],"perturbations":[102],"by":[103],"leveraging":[104],"information":[105],"both":[107],"main":[109,129],"task":[110,130],"auxiliary":[112],"tasks,":[113],"combining":[114],"them":[115],"through":[116,190],"random":[118],"weighted":[119],"summation.":[120],"This":[121],"approach":[122],"preserves":[123],"primary":[125],"directionality":[126],"while":[132,167],"introducing":[133],"variability":[134],"in":[135,164,205],"directions,":[137],"enabling":[138],"discovery":[140],"diverse":[142],"defensive":[147],"perspective.":[148],"Extensive":[149],"experiments":[150,192],"five":[152],"benchmark":[153],"datasets":[154],"show":[155],"non-optimized":[158],"MP":[159,170,204],"surpasses":[160],"existing":[161],"AT":[162,196],"methods":[163],"several":[165],"settings,":[166],"optimized":[169],"consistently":[171],"achieves":[172],"highest":[174],"robustness.":[175],"We":[176],"further":[177],"analyze":[178],"diversity,":[180],"conduct":[181],"ablation":[182],"studies":[183],"explain":[185],"MP\u2019s":[186],"effectiveness.":[187],"addition,":[189],"combination":[191],"with":[193],"state-of-the-art":[195],"confirmed":[199],"promising":[201],"potential":[202],"enhancing":[206],"model":[207],"robustness":[208],"outlined":[210],"directions":[211],"future":[213],"research.":[214]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-03-18T00:00:00"}
