{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T16:37:22Z","timestamp":1781282242021,"version":"3.54.1"},"reference-count":128,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2021,10,8]],"date-time":"2021-10-08T00:00:00Z","timestamp":1633651200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Data Science"],"published-print":{"date-parts":[[2021,10,13]]},"abstract":"<jats:p>Combining and analysing sensitive data from multiple sources offers considerable potential for knowledge discovery. However, there are a number of issues that pose problems for such analyses, including technical barriers, privacy restrictions, security concerns, and trust issues. Privacy-preserving distributed data mining techniques (PPDDM) aim to overcome these challenges by extracting knowledge from partitioned data while minimizing the release of sensitive information. This paper reports the results and findings of a systematic review of PPDDM techniques from 231 scientific articles published in the past 20 years. We summarize the state of the art, compare the problems they address, and identify the outstanding challenges in the field. This review identifies the consequence of the lack of standard criteria to evaluate new PPDDM methods and proposes comprehensive evaluation criteria with 10 key factors. We discuss the ambiguous definitions of privacy and confusion between privacy and security in the field, and provide suggestions of how to make a clear and applicable privacy description for new PPDDM techniques. The findings from our review enhance the understanding of the challenges of applying theoretical PPDDM methods to real-life use cases, and the importance of involving legal-ethical and social experts in implementing PPDDM methods. This comprehensive review will serve as a helpful guide to past research and future opportunities in the area of PPDDM.<\/jats:p>","DOI":"10.3233\/ds-210036","type":"journal-article","created":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T11:37:56Z","timestamp":1635507476000},"page":"121-150","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":12,"title":["A systematic review on privacy-preserving distributed data mining"],"prefix":"10.1177","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8325-8848","authenticated-orcid":false,"given":"Chang","family":"Sun","sequence":"first","affiliation":[{"name":"Institute of Data Science, Faculty of Science and Engineering, Maastricht University, Maastricht, The Netherlands."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8314-0305","authenticated-orcid":false,"given":"Lianne","family":"Ippel","sequence":"additional","affiliation":[{"name":"Institute of Data Science, Faculty of Science and Engineering, Maastricht University, Maastricht, The Netherlands."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0422-7996","authenticated-orcid":false,"given":"Andre","family":"Dekker","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4727-9435","authenticated-orcid":false,"given":"Michel","family":"Dumontier","sequence":"additional","affiliation":[{"name":"Institute of Data Science, Faculty of Science and Engineering, Maastricht University, Maastricht, The Netherlands."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2548-0330","authenticated-orcid":false,"given":"Johan","family":"van Soest","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands and Brightlands Institute of Smart Society (BISS), Faculty of Science and Engineering, Maastricht University, Maastricht\/Heerlen, The Netherlands."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2021,10,8]]},"reference":[{"key":"ref001","doi-asserted-by":"publisher","DOI":"10.1186\/2193-1801-4-1"},{"key":"ref002","doi-asserted-by":"publisher","DOI":"10.1145\/76894.76895"},{"key":"ref003","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocy061"},{"key":"ref004","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44634-6_16"},{"key":"ref005","doi-asserted-by":"publisher","DOI":"10.1145\/100216.100287"},{"key":"ref006","doi-asserted-by":"publisher","DOI":"10.1186\/s13073-016-0388-7"},{"key":"ref007","doi-asserted-by":"publisher","DOI":"10.1145\/3335741.3335756"},{"key":"ref008","doi-asserted-by":"publisher","DOI":"10.4018\/978-1-4666-8387-7.CH014"},{"key":"ref009","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-70992-5_8"},{"key":"ref010","doi-asserted-by":"publisher","DOI":"10.1007\/11546849_41"},{"key":"ref011","unstructured":"A.\u00a0Bhowmick, J.\u00a0Duchi, J.\u00a0Freudiger, G.\u00a0Kapoor and R.\u00a0Rogers, Protection against reconstruction and its applications in private federated learning, 2018, arXiv preprint arXiv:1812.00984."},{"key":"ref012","unstructured":"Binnenlandse\u00a0Zaken en\u00a0Koninkrijksrelaties, Wet van 21 juli 2007, houdende algemene bepalingen betreffende de toekenning, het beheer en het gebruik van het burgerservicenummer (wet algemene bepalingen burgerservicenummer), 2018-07-28. https:\/\/wetten.overheid.nl\/jci1.3:c:BWBR0022428&z=2018-07-28&g=2018-07-28."},{"key":"ref013","unstructured":"A.\u00a0Botchkarev, Performance metrics (error measures) in machine learning regression, forecasting and prognostics: Properties and typology, 2018, arXiv preprint arXiv:1809.03006."},{"key":"ref014","unstructured":"P.K.\u00a0Chan, S.J.\u00a0Stolfo et al., Toward parallel and distributed learning by meta-learning, in: AAAI Workshop in Knowledge Discovery in Databases, 1993, pp.\u00a0227\u2013240. https:\/\/dl.acm.org\/doi\/10.5555\/3000767.3000789#d49627527e1."},{"key":"ref015","doi-asserted-by":"publisher","DOI":"10.1145\/3387107"},{"key":"ref016","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-31164-2"},{"key":"ref017","unstructured":"E.A.\u00a0Clarke, What is preventive medicine? 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