{"id":"https://openalex.org/W2293768274","doi":"https://doi.org/10.1145/1014052.1014066","title":"Adversarial classification","display_name":"Adversarial classification","publication_year":2004,"publication_date":"2004-08-22","ids":{"openalex":"https://openalex.org/W2293768274","doi":"https://doi.org/10.1145/1014052.1014066","mag":"2293768274"},"language":"en","primary_location":{"id":"doi:10.1145/1014052.1014066","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1014052.1014066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5081323769","display_name":"Nilesh Dalvi","orcid":null},"institutions":[{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]},{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nilesh Dalvi","raw_affiliation_strings":["University of Washington - Seattle, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"University of Washington - Seattle, Seattle, WA","institution_ids":["https://openalex.org/I58610484","https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018711331","display_name":"Pedro Domingos","orcid":"https://orcid.org/0000-0003-4523-5631"},"institutions":[{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]},{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pedro Domingos","raw_affiliation_strings":["University of Washington - Seattle, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"University of Washington - Seattle, Seattle, WA","institution_ids":["https://openalex.org/I58610484","https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042262991","display_name":"Mausam Mausam","orcid":"https://orcid.org/0000-0003-4088-4296"},"institutions":[{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]},{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mausam","raw_affiliation_strings":["University of Washington - Seattle, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"University of Washington - Seattle, Seattle, WA","institution_ids":["https://openalex.org/I58610484","https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088663909","display_name":"Sumit Sanghai","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sumit Sanghai","raw_affiliation_strings":["University of Washington - Seattle, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"University of Washington - Seattle, Seattle, WA","institution_ids":["https://openalex.org/I58610484","https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084181171","display_name":"Deepak Kumar Verma","orcid":"https://orcid.org/0000-0001-7177-7632"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deepak Verma","raw_affiliation_strings":["University of Washington - Seattle, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"University of Washington - Seattle, Seattle, WA","institution_ids":["https://openalex.org/I58610484","https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5081323769"],"corresponding_institution_ids":["https://openalex.org/I201448701","https://openalex.org/I58610484"],"apc_list":null,"apc_paid":null,"fwci":8.4753,"has_fulltext":false,"cited_by_count":899,"citation_normalized_percentile":{"value":0.97743846,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"99","last_page":"108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983999729156494,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/classifier","display_name":"Classifier (UML)","score":0.85416179895401},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8038878440856934},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.7774921655654907},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7242037057876587},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5647474527359009},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5068269371986389},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.48300039768218994},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38694262504577637},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3672716021537781},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2983510494232178}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.85416179895401},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8038878440856934},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.7774921655654907},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7242037057876587},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5647474527359009},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5068269371986389},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.48300039768218994},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38694262504577637},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3672716021537781},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2983510494232178}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1145/1014052.1014066","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1014052.1014066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.11.492","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.492","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.washington.edu/homes/pedrod/papers/kdd04.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.137.5487","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.137.5487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.lans.ece.utexas.edu/course/ee380l/05sp/papers/dalvi04adversarial.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.174.6981","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.174.6981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ai.cs.washington.edu/www/media/papers/kdd04.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.302.2454","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.302.2454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://homes.cs.washington.edu/~pedrod/papers/kdd04.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1415442047","https://openalex.org/W1517113043","https://openalex.org/W1542941925","https://openalex.org/W1550206324","https://openalex.org/W1605188341","https://openalex.org/W1648885110","https://openalex.org/W1960351623","https://openalex.org/W2010657328","https://openalex.org/W2011039300","https://openalex.org/W2017337590","https://openalex.org/W2026080185","https://openalex.org/W2048791264","https://openalex.org/W2058732827","https://openalex.org/W2068426846","https://openalex.org/W2084947386","https://openalex.org/W2096942889","https://openalex.org/W2099606292","https://openalex.org/W2108601876","https://openalex.org/W2140785063","https://openalex.org/W2168421438","https://openalex.org/W6606244154","https://openalex.org/W6635846226","https://openalex.org/W6636944375"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W4320018150","https://openalex.org/W2918664383","https://openalex.org/W203812490","https://openalex.org/W4320855730","https://openalex.org/W3123119822","https://openalex.org/W106056076","https://openalex.org/W2135200719","https://openalex.org/W4211142322"],"abstract_inverted_index":{"Essentially":[0],"all":[1],"data":[2,14,38],"mining":[3],"algorithms":[4,99],"assume":[5],"that":[6,119,134],"the":[7,13,35,37,48,56,69,76,88,110,113,123,144,149,152,156,159],"data-generating":[8],"process":[9],"is":[10,32,39,66,81,120],"independent":[11],"of":[12,58,87,151],"miner's":[15],"activities.":[16],"However,":[17],"in":[18,128,143],"many":[19],"domains,":[20,55],"including":[21],"spam":[22,130],"detection,":[23,25,27],"intrusion":[24],"fraud":[26],"surveillance":[28],"and":[29,98,112,115,147],"counter-terrorism,":[30],"this":[31,80,91,101,135],"far":[33],"from":[34],"case:":[36],"actively":[40],"manipulated":[41],"by":[42],"an":[43],"adversary":[44,70],"seeking":[45],"to":[46,72,79,158],"make":[47],"classifier":[49,60,111,118,141,157],"produce":[50,116],"false":[51],"negatives.":[52],"In":[53,90],"these":[54],"performance":[57],"a":[59,95,107,117,129,140],"can":[61,137],"degrade":[62],"rapidly":[63],"after":[64],"it":[65],"deployed,":[67],"as":[68,106],"learns":[71],"defeat":[73],"it.":[74],"Currently":[75],"only":[77],"solution":[78],"repeated,":[82],"manual,":[83],"ad":[84],"hoc":[85],"reconstruction":[86],"classifier.":[89],"paper":[92],"we":[93],"develop":[94],"formal":[96],"framework":[97],"for":[100],"problem.":[102],"We":[103],"view":[104],"classification":[105],"game":[108],"between":[109],"adversary,":[114],"optimal":[121,125],"given":[122],"adversary's":[124,160],"strategy.":[126],"Experiments":[127],"detection":[131],"domain":[132],"show":[133],"approach":[136],"greatly":[138],"outperform":[139],"learned":[142],"standard":[145],"way,":[146],"(within":[148],"parameters":[150],"problem)":[153],"automatically":[154],"adapt":[155],"evolving":[161],"manipulations.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":32},{"year":2024,"cited_by_count":45},{"year":2023,"cited_by_count":84},{"year":2022,"cited_by_count":70},{"year":2021,"cited_by_count":99},{"year":2020,"cited_by_count":91},{"year":2019,"cited_by_count":97},{"year":2018,"cited_by_count":62},{"year":2017,"cited_by_count":41},{"year":2016,"cited_by_count":37},{"year":2015,"cited_by_count":37},{"year":2014,"cited_by_count":25},{"year":2013,"cited_by_count":19},{"year":2012,"cited_by_count":26}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}