{"id":"https://openalex.org/W4390678180","doi":"https://doi.org/10.1109/icsrs59833.2023.10381066","title":"Investigating Lipschitz Constants in Neural Ensemble Models to Improve Adversarial Robustness","display_name":"Investigating Lipschitz Constants in Neural Ensemble Models to Improve Adversarial Robustness","publication_year":2023,"publication_date":"2023-11-22","ids":{"openalex":"https://openalex.org/W4390678180","doi":"https://doi.org/10.1109/icsrs59833.2023.10381066"},"language":"en","primary_location":{"id":"doi:10.1109/icsrs59833.2023.10381066","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icsrs59833.2023.10381066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 7th International Conference on System Reliability and Safety (ICSRS)","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/A5041797757","display_name":"Minal Suresh Patil","orcid":"https://orcid.org/0000-0003-0026-5503"},"institutions":[{"id":"https://openalex.org/I90267481","display_name":"Ume\u00e5 University","ror":"https://ror.org/05kb8h459","country_code":"SE","type":"education","lineage":["https://openalex.org/I90267481"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Minal Suresh Patil","raw_affiliation_strings":["Umeå universitet,Department of Computing Science,Umeå,Sweden"],"affiliations":[{"raw_affiliation_string":"Umeå universitet,Department of Computing Science,Umeå,Sweden","institution_ids":["https://openalex.org/I90267481"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028199120","display_name":"Kary Fr\u00e4mling","orcid":"https://orcid.org/0000-0002-8078-5172"},"institutions":[{"id":"https://openalex.org/I90267481","display_name":"Ume\u00e5 University","ror":"https://ror.org/05kb8h459","country_code":"SE","type":"education","lineage":["https://openalex.org/I90267481"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Kary Fr\u00e4mling","raw_affiliation_strings":["Umeå universitet,Department of Computing Science,Umeå,Sweden"],"affiliations":[{"raw_affiliation_string":"Umeå universitet,Department of Computing Science,Umeå,Sweden","institution_ids":["https://openalex.org/I90267481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041797757"],"corresponding_institution_ids":["https://openalex.org/I90267481"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1870972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":null,"first_page":"434","last_page":"438"},"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/T11515","display_name":"Bacillus and Francisella bacterial research","score":0.9686999917030334,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9569000005722046,"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/robustness","display_name":"Robustness (evolution)","score":0.8091112375259399},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.8007245659828186},{"id":"https://openalex.org/keywords/lipschitz-continuity","display_name":"Lipschitz continuity","score":0.7645201086997986},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7168063521385193},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.687695324420929},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6066591143608093},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5379214286804199},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5009016990661621},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.47856858372688293},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.4694969952106476},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43555307388305664},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.4213990569114685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22726410627365112}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8091112375259399},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8007245659828186},{"id":"https://openalex.org/C22324862","wikidata":"https://www.wikidata.org/wiki/Q652707","display_name":"Lipschitz continuity","level":2,"score":0.7645201086997986},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7168063521385193},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.687695324420929},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6066591143608093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5379214286804199},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5009016990661621},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.47856858372688293},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.4694969952106476},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43555307388305664},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.4213990569114685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22726410627365112},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsrs59833.2023.10381066","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icsrs59833.2023.10381066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 7th International Conference on System Reliability and Safety (ICSRS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W1673923490","https://openalex.org/W1731081199","https://openalex.org/W1945616565","https://openalex.org/W1990322717","https://openalex.org/W2180612164","https://openalex.org/W2243397390","https://openalex.org/W2618235498","https://openalex.org/W2798302089","https://openalex.org/W2963389226","https://openalex.org/W2963857521","https://openalex.org/W3009559573","https://openalex.org/W3022782115","https://openalex.org/W3042135962","https://openalex.org/W4212883601","https://openalex.org/W4317466250","https://openalex.org/W6637618735","https://openalex.org/W6738369334","https://openalex.org/W6756052093","https://openalex.org/W6763711611","https://openalex.org/W6774356374","https://openalex.org/W6780154528"],"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":{"This":[0],"work":[1],"investigates":[2],"the":[3,9,42,68,87],"relationship":[4],"between":[5],"adversarial":[6,37,55,62,72],"robustness":[7],"and":[8,20,36,57,74,89,97,109],"local":[10,43],"Lipschitz":[11,44],"constant":[12],"in":[13],"ensemble":[14,28,83,111],"neural":[15,29],"network":[16,30],"frameworks,":[17],"namely":[18],"bagging":[19],"stacking.":[21],"Capitalising":[22],"on":[23,86],"this,":[24],"we":[25],"introduce":[26],"an":[27,82],"design":[31],"that":[32],"improves":[33],"both":[34,47],"accuracy":[35],"resilience.":[38],"We":[39],"theoretically":[40],"obtain":[41],"constants":[45],"for":[46,61,70,81],"ensembles,":[48],"offering":[49],"insights":[50],"into":[51],"their":[52],"susceptibility":[53],"to":[54,106],"attacks":[56],"identifying":[58],"architectures":[59],"optimal":[60],"defense.":[63],"Notably,":[64],"our":[65,100],"approach":[66,101],"negates":[67],"need":[69],"specific":[71],"attack":[73],"accommodates":[75],"any":[76],"number":[77],"of":[78],"pre-trained":[79],"networks":[80,108],"architecture.":[84],"Evaluations":[85],"MNIST":[88],"CIFAR-10":[90],"datasets":[91],"against":[92],"white-box":[93],"attacks,":[94],"specifically":[95],"FGSM":[96],"PGD,":[98],"show":[99],"is":[102],"adversarially":[103],"robust":[104],"compared":[105],"standalone":[107],"vanilla":[110],"architectures.":[112]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}