{"id":"https://openalex.org/W7164191151","doi":"https://doi.org/10.48550/arxiv.2606.10091","title":"SoK: Colluding Adversaries in Machine Learning Pipelines","display_name":"SoK: Colluding Adversaries in Machine Learning Pipelines","publication_year":2026,"publication_date":"2026-06-08","ids":{"openalex":"https://openalex.org/W7164191151","doi":"https://doi.org/10.48550/arxiv.2606.10091"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.10091","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.10091","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.10091","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037812896","display_name":"Vasisht Duddu","orcid":"https://orcid.org/0000-0003-2138-4341"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duddu, Vasisht","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138346786","display_name":"Lipeng He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Lipeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036316299","display_name":"Asim Waheed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Waheed, Asim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138376464","display_name":"N. Asokan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Asokan, N.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"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":0.9962000250816345,"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":0.9962000250816345,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.000699999975040555,"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":0.0006000000284984708,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/collusion","display_name":"Collusion","score":0.9659000039100647},{"id":"https://openalex.org/keywords/conjecture","display_name":"Conjecture","score":0.532800018787384},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.3935999870300293},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.37610000371932983},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.32420000433921814}],"concepts":[{"id":"https://openalex.org/C2781198186","wikidata":"https://www.wikidata.org/wiki/Q701521","display_name":"Collusion","level":2,"score":0.9659000039100647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6833000183105469},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5422999858856201},{"id":"https://openalex.org/C2780990831","wikidata":"https://www.wikidata.org/wiki/Q319141","display_name":"Conjecture","level":2,"score":0.532800018787384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5012000203132629},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.40450000762939453},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.3935999870300293},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.37610000371932983},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C2780182762","wikidata":"https://www.wikidata.org/wiki/Q1630279","display_name":"Guideline","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.10091","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.10091","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.10091","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.10091","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5655081868171692,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Machine":[0],"learning":[1],"(ML)":[2],"models":[3],"are":[4],"susceptible":[5],"to":[6,28,37,43,81,94],"various":[7],"security,":[8],"privacy,":[9],"and":[10,20,42,60,63,102],"fairness":[11],"risks.":[12],"Adversaries":[13],"with":[14],"different":[15],"characteristics":[16,113],"(i.e.,":[17],"objectives,":[18],"knowledge,":[19],"capabilities)":[21],"can":[22],"collude":[23],"by":[24],"executing":[25],"one":[26],"attack":[27],"amplify":[29],"others.":[30],"Existing":[31],"work":[32],"lacks":[33],"a":[34,53,79],"systematic":[35],"framework":[36,54,69],"explore":[38],"collusion":[39,56,74,87],"among":[40,65],"adversaries,":[41,62],"study":[44],"the":[45,48,84,115],"implications":[46],"of":[47],"adversaries'":[49,112],"characteristics.":[50],"We":[51,77,91],"present":[52],"covering":[55],"(a)":[57],"between":[58,75],"train-":[59],"inference-time":[61,66],"(b)":[64],"adversaries.":[67,76],"Our":[68],"accounts":[70],"for":[71,86,117],"factors":[72],"enabling":[73,89],"propose":[78],"guideline":[80],"conjecture":[82,98],"about":[83,99],"potential":[85,116],"using":[88],"factors.":[90],"use":[92],"it":[93],"explain":[95],"prior":[96],"work,":[97],"unexplored":[100],"collusions,":[101],"empirically":[103],"validate":[104],"five":[105],"such":[106],"cases.":[107],"Finally,":[108],"we":[109],"discuss":[110],"how":[111],"influence":[114],"collusion.":[118]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-11T00:00:00"}