{"id":"https://openalex.org/W2966764754","doi":"https://doi.org/10.24963/ijcai.2019/649","title":"Real-Time Adversarial Attacks","display_name":"Real-Time Adversarial Attacks","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2966764754","doi":"https://doi.org/10.24963/ijcai.2019/649","mag":"2966764754"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/649","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/649","pdf_url":"https://www.ijcai.org/proceedings/2019/0649.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0649.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067285379","display_name":"Yuan Gong","orcid":"https://orcid.org/0000-0002-4537-0078"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuan Gong","raw_affiliation_strings":["University of Notre Dame"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100732746","display_name":"Boyang Li","orcid":"https://orcid.org/0000-0002-6230-2376"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Boyang Li","raw_affiliation_strings":["University of Notre Dame"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019362963","display_name":"Christian Poellabauer","orcid":"https://orcid.org/0000-0002-0599-7941"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christian Poellabauer","raw_affiliation_strings":["University of Notre Dame"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000141831","display_name":"Yiyu Shi","orcid":"https://orcid.org/0000-0002-6788-9823"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiyu Shi","raw_affiliation_strings":["University of Notre Dame"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5067285379"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":3.5004,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.94254364,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4672","last_page":"4680"},"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":0.9747999906539917,"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/T10683","display_name":"Mass Spectrometry Techniques and Applications","score":0.9416000247001648,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.834030032157898},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8110695481300354},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5450752377510071},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5167259573936462},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5097967982292175},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.48855170607566833},{"id":"https://openalex.org/keywords/adversarial-machine-learning","display_name":"Adversarial machine learning","score":0.4741777181625366},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42631039023399353},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.41957804560661316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41814830899238586},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33650416135787964},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09209093451499939}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.834030032157898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8110695481300354},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5450752377510071},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5167259573936462},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5097967982292175},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.48855170607566833},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.4741777181625366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42631039023399353},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.41957804560661316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41814830899238586},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33650416135787964},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09209093451499939},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/649","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/649","pdf_url":"https://www.ijcai.org/proceedings/2019/0649.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/649","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/649","pdf_url":"https://www.ijcai.org/proceedings/2019/0649.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2966764754.pdf","grobid_xml":"https://content.openalex.org/works/W2966764754.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1515851193","https://openalex.org/W1522301498","https://openalex.org/W1673923490","https://openalex.org/W1931877416","https://openalex.org/W1945616565","https://openalex.org/W2058857176","https://openalex.org/W2243397390","https://openalex.org/W2407023693","https://openalex.org/W2543927648","https://openalex.org/W2744095836","https://openalex.org/W2767951891","https://openalex.org/W2782403400","https://openalex.org/W2795031232","https://openalex.org/W2797583228","https://openalex.org/W2799194071","https://openalex.org/W2809943552","https://openalex.org/W2923292931","https://openalex.org/W2963058500","https://openalex.org/W2964301649","https://openalex.org/W2972706975","https://openalex.org/W3103557498","https://openalex.org/W4300434632"],"related_works":["https://openalex.org/W3048732067","https://openalex.org/W4383468834","https://openalex.org/W4283221438","https://openalex.org/W2900159906","https://openalex.org/W4384648009","https://openalex.org/W4287828318","https://openalex.org/W2406556600","https://openalex.org/W4380352238","https://openalex.org/W3126470649","https://openalex.org/W2930249865"],"abstract_inverted_index":{"In":[0,107],"recent":[1],"years,":[2],"many":[3],"efforts":[4],"have":[5],"demonstrated":[6],"that":[7],"modern":[8],"machine":[9,118],"learning":[10,119],"algorithms":[11],"are":[12,34,72],"vulnerable":[13],"to":[14,75,90,98],"adversarial":[15,114],"attacks,":[16],"where":[17,42,77],"small,":[18],"but":[19],"carefully":[20],"crafted,":[21],"perturbations":[22,97],"on":[23,40],"the":[24,43,54,67,78,99,105],"input":[25],"can":[26,52],"make":[27],"them":[28],"fail.":[29],"While":[30],"these":[31],"attack":[32,70,115],"methods":[33],"very":[35],"effective,":[36],"they":[37],"only":[38,88],"focus":[39],"scenarios":[41],"target":[44,79],"model":[45,80],"takes":[46,81],"static":[47],"input,":[48,83],"i.e.,":[49,84],"an":[50,85],"attacker":[51,86],"observe":[53,91],"entire":[55],"original":[56],"sample":[57],"and":[58,95],"then":[59],"add":[60,96],"a":[61,112],"perturbation":[62],"at":[63],"any":[64],"point":[65],"of":[66,104],"sample.":[68],"These":[69],"approaches":[71],"not":[73],"applicable":[74],"situations":[76],"streaming":[82,122],"is":[87],"able":[89],"past":[92],"data":[93,102],"points":[94,103],"remaining":[100],"(unobserved)":[101],"input.":[106],"this":[108],"paper,":[109],"we":[110],"propose":[111],"real-time":[113],"scheme":[116],"for":[117],"models":[120],"with":[121],"inputs.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}