{"id":"https://openalex.org/W2900593276","doi":"https://doi.org/10.1145/3243734.3278520","title":"Privacy-Preserving Boosting with Random Linear Classifiers","display_name":"Privacy-Preserving Boosting with Random Linear Classifiers","publication_year":2018,"publication_date":"2018-10-15","ids":{"openalex":"https://openalex.org/W2900593276","doi":"https://doi.org/10.1145/3243734.3278520","mag":"2900593276"},"language":"en","primary_location":{"id":"doi:10.1145/3243734.3278520","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3243734.3278520","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security","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/A5052897959","display_name":"Sagar Sharma","orcid":"https://orcid.org/0000-0002-6667-4724"},"institutions":[{"id":"https://openalex.org/I19648265","display_name":"Wright State University","ror":"https://ror.org/04qk6pt94","country_code":"US","type":"education","lineage":["https://openalex.org/I19648265"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sagar Sharma","raw_affiliation_strings":["Wright State University, Dayton, OH, USA"],"affiliations":[{"raw_affiliation_string":"Wright State University, Dayton, OH, USA","institution_ids":["https://openalex.org/I19648265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002572745","display_name":"Keke Chen","orcid":"https://orcid.org/0000-0002-9996-156X"},"institutions":[{"id":"https://openalex.org/I19648265","display_name":"Wright State University","ror":"https://ror.org/04qk6pt94","country_code":"US","type":"education","lineage":["https://openalex.org/I19648265"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keke Chen","raw_affiliation_strings":["Wright State University, Dayton, OH, USA"],"affiliations":[{"raw_affiliation_string":"Wright State University, Dayton, OH, USA","institution_ids":["https://openalex.org/I19648265"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5052897959"],"corresponding_institution_ids":["https://openalex.org/I19648265"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.13033968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2294","last_page":"2296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T10237","display_name":"Cryptography and Data Security","score":0.9998000264167786,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9861000180244446,"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/homomorphic-encryption","display_name":"Homomorphic encryption","score":0.8384685516357422},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.8086585998535156},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7944881916046143},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.5477820634841919},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.5354772806167603},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48502296209335327},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4665375053882599},{"id":"https://openalex.org/keywords/cryptographic-primitive","display_name":"Cryptographic primitive","score":0.43359941244125366},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4160362482070923},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36401131749153137},{"id":"https://openalex.org/keywords/cryptographic-protocol","display_name":"Cryptographic protocol","score":0.3596000075340271},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2187795341014862}],"concepts":[{"id":"https://openalex.org/C158338273","wikidata":"https://www.wikidata.org/wiki/Q2154943","display_name":"Homomorphic encryption","level":3,"score":0.8384685516357422},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8086585998535156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7944881916046143},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.5477820634841919},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.5354772806167603},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48502296209335327},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4665375053882599},{"id":"https://openalex.org/C15927051","wikidata":"https://www.wikidata.org/wiki/Q246593","display_name":"Cryptographic primitive","level":4,"score":0.43359941244125366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4160362482070923},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36401131749153137},{"id":"https://openalex.org/C33884865","wikidata":"https://www.wikidata.org/wiki/Q1254335","display_name":"Cryptographic protocol","level":3,"score":0.3596000075340271},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2187795341014862}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3243734.3278520","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3243734.3278520","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W133884053","https://openalex.org/W1971991172","https://openalex.org/W2033050620","https://openalex.org/W2047370889","https://openalex.org/W2051267297","https://openalex.org/W2535690855","https://openalex.org/W2701059868","https://openalex.org/W2949777041"],"related_works":["https://openalex.org/W2949937073","https://openalex.org/W1586131529","https://openalex.org/W3028834223","https://openalex.org/W31845566","https://openalex.org/W609944529","https://openalex.org/W3213139219","https://openalex.org/W4287714351","https://openalex.org/W2225954419","https://openalex.org/W12749313","https://openalex.org/W2037113620"],"abstract_inverted_index":{"We":[0,97,118],"propose":[1],"SecureBoost,":[2],"a":[3,77],"privacy-preserving":[4],"predictive":[5],"modeling":[6],"framework,":[7],"that":[8,120],"allows":[9],"service":[10],"providers":[11],"(SPs)":[12],"to":[13,48],"build":[14],"powerful":[15],"boosting":[16,125],"models":[17,62,75,126],"over":[18],"encrypted":[19],"or":[20,93],"randomly":[21],"masked":[22],"user":[23],"submitted":[24],"data.":[25],"SecureBoost":[26,121],"uses":[27],"random":[28,116],"linear":[29],"classifiers":[30],"(RLCs)":[31],"as":[32],"the":[33,45,50,53,60,66,70,73,90],"base":[34,61,74],"classifiers.":[35],"A":[36],"Cryptographic":[37],"Service":[38],"Provider":[39],"(CSP)":[40],"manages":[41],"keys":[42],"and":[43,65,76,104,115],"assists":[44],"SP's":[46],"processing":[47],"reduce":[49],"complexity":[51],"of":[52,72,101,108],"protocol":[54],"constructions.":[55],"The":[56],"SP":[57],"learns":[58,68,123],"only":[59,69],"(i.e.,":[63],"RLCs)":[64],"CSP":[67],"weights":[71],"limited":[78],"leakage":[79],"function.":[80],"This":[81],"separated":[82],"parameter":[83],"holding":[84],"avoids":[85],"any":[86],"party":[87],"from":[88,127],"abusing":[89],"final":[91],"model":[92],"conducting":[94],"model-based":[95],"attacks.":[96],"evaluate":[98],"two":[99],"constructions":[100],"SecureBoost:":[102],"HE+GC":[103],"SecSh+GC":[105],"using":[106],"combinations":[107],"primitives":[109],"-":[110],"homomorphic":[111],"encryption,":[112],"garbled":[113],"circuits,":[114],"masking.":[117],"show":[119],"efficiently":[122],"high-quality":[124],"protected":[128],"user-generated":[129],"data":[130],"with":[131],"practical":[132],"costs.":[133]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
