{"id":"https://openalex.org/W4411091041","doi":"https://doi.org/10.1007/s10994-025-06799-w","title":"Differentially-private data synthetisation for efficient re-identification risk control","display_name":"Differentially-private data synthetisation for efficient re-identification risk control","publication_year":2025,"publication_date":"2025-06-06","ids":{"openalex":"https://openalex.org/W4411091041","doi":"https://doi.org/10.1007/s10994-025-06799-w"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-025-06799-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-025-06799-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-025-06799-w.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-025-06799-w.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044261553","display_name":"T\u00e2nia Carvalho","orcid":"https://orcid.org/0000-0002-5283-5013"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]}],"countries":["PT"],"is_corresponding":true,"raw_author_name":"T\u00e2nia Carvalho","raw_affiliation_strings":["University of Porto, Faculty of Sciences, Porto, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Porto, Faculty of Sciences, Porto, Portugal","institution_ids":["https://openalex.org/I182534213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047689411","display_name":"Nuno Moniz","orcid":"https://orcid.org/0000-0003-4322-1076"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]},{"id":"https://openalex.org/I1295409710","display_name":"History of Science Society","ror":"https://ror.org/03fz1tt45","country_code":"US","type":"other","lineage":["https://openalex.org/I1295409710"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nuno Moniz","raw_affiliation_strings":["University of Notre Dame, Lucy Family Institute for Data & Society, Notre Dame, Indiana, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Lucy Family Institute for Data & Society, Notre Dame, Indiana, USA","institution_ids":["https://openalex.org/I107639228","https://openalex.org/I1295409710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048190616","display_name":"Lu\u00eds Antunes","orcid":"https://orcid.org/0000-0002-9988-594X"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Lu\u00eds Antunes","raw_affiliation_strings":["TekPrivacy, Porto, Portugal","University of Porto, Faculty of Sciences, Porto, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TekPrivacy, Porto, Portugal","institution_ids":[]},{"raw_affiliation_string":"University of Porto, Faculty of Sciences, Porto, Portugal","institution_ids":["https://openalex.org/I182534213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068157871","display_name":"Nitesh V. Chawla","orcid":"https://orcid.org/0000-0003-3932-5956"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]},{"id":"https://openalex.org/I1295409710","display_name":"History of Science Society","ror":"https://ror.org/03fz1tt45","country_code":"US","type":"other","lineage":["https://openalex.org/I1295409710"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nitesh Chawla","raw_affiliation_strings":["University of Notre Dame, Lucy Family Institute for Data & Society, Notre Dame, Indiana, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Lucy Family Institute for Data & Society, Notre Dame, Indiana, USA","institution_ids":["https://openalex.org/I107639228","https://openalex.org/I1295409710"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5044261553"],"corresponding_institution_ids":["https://openalex.org/I182534213"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":1.2041,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83653274,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"114","issue":"7","first_page":null,"last_page":null},"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":0.9991000294685364,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9980000257492065,"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/identification","display_name":"Identification (biology)","score":0.6076036095619202},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5745211243629456},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.45858335494995117},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3892737627029419},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3481210172176361}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6076036095619202},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5745211243629456},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.45858335494995117},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3892737627029419},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3481210172176361},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10994-025-06799-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-025-06799-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-025-06799-w.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10994-025-06799-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-025-06799-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-025-06799-w.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320324086","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612"},{"id":"https://openalex.org/F4320334779","display_name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","ror":"https://ror.org/00snfqn58"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411091041.pdf","grobid_xml":"https://content.openalex.org/works/W4411091041.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W22424597","https://openalex.org/W1982183556","https://openalex.org/W1992286709","https://openalex.org/W1995341919","https://openalex.org/W2109426455","https://openalex.org/W2113242816","https://openalex.org/W2115209166","https://openalex.org/W2119067110","https://openalex.org/W2132791018","https://openalex.org/W2132862423","https://openalex.org/W2148143831","https://openalex.org/W2295598076","https://openalex.org/W2443241466","https://openalex.org/W2565167788","https://openalex.org/W2903362744","https://openalex.org/W2908109788","https://openalex.org/W2967880504","https://openalex.org/W2977787364","https://openalex.org/W2990138404","https://openalex.org/W3007878074","https://openalex.org/W3038283795","https://openalex.org/W3080084288","https://openalex.org/W3090899011","https://openalex.org/W3158777740","https://openalex.org/W3165064799","https://openalex.org/W3197295672","https://openalex.org/W4223929858","https://openalex.org/W4234726042","https://openalex.org/W4238014149","https://openalex.org/W4323349011","https://openalex.org/W4361303853","https://openalex.org/W6606645873","https://openalex.org/W6607941208","https://openalex.org/W6629461242","https://openalex.org/W6657138077","https://openalex.org/W6675354045","https://openalex.org/W6765451912","https://openalex.org/W6787376386"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Abstract":[0],"Protecting":[1],"user":[2],"data":[3,28,57,92],"privacy":[4,99,121,144],"can":[5],"be":[6],"achieved":[7],"via":[8,94],"many":[9],"methods,":[10,135],"from":[11],"statistical":[12],"transformations":[13],"to":[14,47,73,101,129],"generative":[15,137],"models.":[16],"However,":[17],"they":[18],"all":[19],"have":[20],"critical":[21],"drawbacks.":[22],"For":[23],"example,":[24],"creating":[25],"a":[26,70,84,158,164],"transformed":[27],"set":[29],"using":[30],"traditional":[31,131],"techniques":[32],"is":[33,114,163],"highly":[34],"time-consuming.":[35],"Also,":[36],"recent":[37],"deep":[38],"learning-based":[39],"solutions":[40,54],"require":[41],"significant":[42],"computational":[43],"resources":[44],"in":[45,120],"addition":[46],"long":[48],"training":[49],"phases,":[50],"and":[51,77,123,132,142,162],"differentially":[52],"private-based":[53],"may":[55],"undermine":[56],"utility.":[58],"In":[59],"this":[60],"paper,":[61],"we":[62],"propose":[63],"$$\\epsilon$$":[64,108],"<mml:math":[65,109],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\">":[66,110],"<mml:mi>\u03f5</mml:mi>":[67,111],"</mml:math>":[68,112],"-PrivateSMOTE,":[69],"technique":[71],"designed":[72],"protect":[74],"against":[75],"re-identification":[76,86],"linkage":[78],"attacks,":[79],"particularly":[80],"addressing":[81],"cases":[82],"with":[83,97],"high":[85,169],"risk.":[87],"Our":[88],"proposal":[89],"combines":[90],"synthetic":[91],"generation":[93],"noise-induced":[95],"interpolation":[96],"differential":[98,143],"principles":[100],"obfuscate":[102],"high-risk":[103],"cases.":[104],"We":[105,146],"demonstrate":[106],"how":[107,149],"-PrivateSMOTE":[113],"capable":[115],"of":[116,160],"achieving":[117],"competitive":[118],"results":[119],"risk":[122],"better":[124],"predictive":[125],"performance":[126,170],"when":[127],"compared":[128],"multiple":[130],"state-of-the-art":[133],"privacy-preservation":[134],"including":[136],"adversarial":[138],"networks,":[139],"variational":[140],"autoencoders,":[141],"baselines.":[145],"also":[147],"show":[148],"our":[150],"method":[151],"improves":[152],"time":[153],"requirements":[154],"by":[155],"at":[156],"least":[157],"factor":[159],"9":[161],"resource-efficient":[165],"solution":[166],"that":[167],"ensures":[168],"without":[171],"specialised":[172],"hardware.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}
