{"id":"https://openalex.org/W4405440624","doi":"https://doi.org/10.1109/pst62714.2024.10788045","title":"Effectiveness of Privacy-Preserving Algorithms for Large Language Models: A Benchmark Analysis","display_name":"Effectiveness of Privacy-Preserving Algorithms for Large Language Models: A Benchmark Analysis","publication_year":2024,"publication_date":"2024-08-28","ids":{"openalex":"https://openalex.org/W4405440624","doi":"https://doi.org/10.1109/pst62714.2024.10788045"},"language":"en","primary_location":{"id":"doi:10.1109/pst62714.2024.10788045","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pst62714.2024.10788045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 21st Annual International Conference on Privacy, Security and Trust (PST)","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/A5031309020","display_name":"Jinglin Sun","orcid":"https://orcid.org/0000-0003-0395-6254"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jinglin Sun","raw_affiliation_strings":["School of Computer Science, University of Sydney"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Sydney","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022818942","display_name":"Basem Suleiman","orcid":"https://orcid.org/0000-0003-2674-0253"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Basem Suleiman","raw_affiliation_strings":["School of Computer Science and Engineering, The University of New South Wales"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, The University of New South Wales","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051193312","display_name":"Imdad Ullah","orcid":"https://orcid.org/0000-0002-8188-2601"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Imdad Ullah","raw_affiliation_strings":["School of Computer Science, University of Sydney"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Sydney","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6109,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.75672757,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9704999923706055,"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":0.9704999923706055,"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/computer-science","display_name":"Computer science","score":0.7685821056365967},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7441938519477844},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4525817632675171},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.328837513923645}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7685821056365967},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7441938519477844},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4525817632675171},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.328837513923645},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pst62714.2024.10788045","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pst62714.2024.10788045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 21st Annual International Conference on Privacy, Security and Trust (PST)","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":15,"referenced_works":["https://openalex.org/W2473418344","https://openalex.org/W2911978475","https://openalex.org/W2998378988","https://openalex.org/W3173528555","https://openalex.org/W4230319711","https://openalex.org/W4319780902","https://openalex.org/W4367047191","https://openalex.org/W4385573200","https://openalex.org/W4394828356","https://openalex.org/W4402671911","https://openalex.org/W4402683027","https://openalex.org/W6763393573","https://openalex.org/W6778883912","https://openalex.org/W6787335730","https://openalex.org/W6810332117"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2051487156","https://openalex.org/W2028665553","https://openalex.org/W2086519370"],"abstract_inverted_index":{"Recently,":[0],"several":[1],"privacy-preserving":[2,52,79,89,146],"algorithms":[3,9,36,53,80,90,147],"for":[4,13,47,60,148],"NLP":[5],"have":[6],"emerged.":[7],"These":[8],"can":[10,17],"be":[11,72],"suitable":[12],"LLMs":[14,62,98,156],"as":[15],"they":[16],"protect":[18],"both":[19],"training":[20,56,92],"and":[21,57,81,93,142],"query":[22,58,94],"data.":[23],"However,":[24],"there":[25],"is":[26,69],"no":[27],"benchmark":[28,45,68,84],"exists":[29],"to":[30,39,55,71,76,138,151],"guide":[31],"the":[32,49,88,104,108,120,125,140,152,161],"evaluation":[33,143],"of":[34,51,127,144,154,163],"these":[35],"when":[37,96,131],"applied":[38,54],"LLMs.":[40,82],"This":[41,135],"paper":[42],"presents":[43],"a":[44,113],"framework":[46],"evaluating":[48],"effectiveness":[50,122],"data":[59,95],"fine-tuning":[61,97],"under":[63],"various":[64,100],"scenarios.":[65,101],"The":[66,83],"proposed":[67],"designed":[70],"transferable,":[73],"enabling":[74],"researchers":[75],"assess":[77],"other":[78],"focuses":[85],"on":[86,91,107],"assessing":[87],"in":[99],"We":[102],"evaluated":[103],"Santext+":[105],"algorithm":[106,133],"open-source":[109],"Llama2-7b":[110],"LLM":[111],"using":[112],"sensitive":[114,164],"medical":[115],"transcription":[116],"dataset.":[117],"Results":[118],"demonstrate":[119],"algorithm's":[121],"while":[123],"highlighting":[124],"importance":[126],"considering":[128],"specific":[129],"situations":[130],"determining":[132],"parameters.":[134],"work":[136],"aims":[137],"facilitate":[139],"development":[141],"effective":[145],"LLMs,":[149],"contributing":[150],"creation":[153],"trusted":[155],"that":[157],"mitigate":[158],"concerns":[159],"regarding":[160],"misuse":[162],"information.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}