{"id":"https://openalex.org/W4410068131","doi":"https://doi.org/10.1145/3715014.3724042","title":"Poster Abstract: Compromising Federated Medical AI-Backdoor Risks in Prompt Learning","display_name":"Poster Abstract: Compromising Federated Medical AI-Backdoor Risks in Prompt Learning","publication_year":2025,"publication_date":"2025-05-04","ids":{"openalex":"https://openalex.org/W4410068131","doi":"https://doi.org/10.1145/3715014.3724042"},"language":"en","primary_location":{"id":"doi:10.1145/3715014.3724042","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3715014.3724042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems","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/A5044260416","display_name":"Momin Ahmad Khan","orcid":"https://orcid.org/0000-0002-6009-514X"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Momin Ahmad Khan","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018307186","display_name":"Yasra Chandio","orcid":"https://orcid.org/0000-0002-3436-6452"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yasra Chandio","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114402613","display_name":"Eugene Bagdasarian","orcid":"https://orcid.org/0000-0002-7994-6469"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eugene Bagdasarian","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038455798","display_name":"Fatima M. Anwar","orcid":"https://orcid.org/0000-0001-7119-7232"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fatima Anwar","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, USA","institution_ids":["https://openalex.org/I24603500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044260416"],"corresponding_institution_ids":["https://openalex.org/I24603500"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04248463,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"630","last_page":"631"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9984999895095825,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9984999895095825,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9876000285148621,"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/backdoor","display_name":"Backdoor","score":0.9952563047409058},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6860194802284241},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4354930818080902},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.41416096687316895},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4059918522834778}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9952563047409058},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6860194802284241},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4354930818080902},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.41416096687316895},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4059918522834778}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3715014.3724042","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3715014.3724042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W3012501605","https://openalex.org/W3086590218","https://openalex.org/W4385627126"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4320031223","https://openalex.org/W4200629851","https://openalex.org/W4394671520","https://openalex.org/W3128233162","https://openalex.org/W4401407399","https://openalex.org/W3176937389","https://openalex.org/W4408069290"],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"the":[3],"security":[4],"vulnerabilities":[5],"of":[6],"prompt-learning-based":[7],"FL":[8,44,49],"systems":[9],"in":[10,25],"a":[11,17,53,65],"healthcare":[12,41],"setting.":[13],"Specifically,":[14],"we":[15],"use":[16],"backdoor":[18,61],"attack":[19,38],"that":[20,47,63],"leverages":[21],"learnable":[22],"prompt":[23],"vectors":[24],"vision-language":[26],"medical":[27,68],"foundation":[28],"models":[29],"to":[30,59,67],"execute":[31],"stealthy":[32],"adversarial":[33],"manipulations.":[34],"We":[35],"evaluate":[36],"our":[37],"across":[39],"diverse":[40],"datasets":[42],"and":[43],"configurations,":[45],"showing":[46],"while":[48],"is":[50,57],"useful":[51],"as":[52],"privacy-preserving":[54],"mechanism,":[55],"it":[56],"susceptible":[58],"targeted":[60],"attacks":[62],"pose":[64],"threat":[66],"applications.":[69]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}