A systematic review on privacy-preserving distributed data mining

Combining and analysing sensitive data from multiple sources offers considerable potential for knowledge discovery. However, there are a number of issues that pose problems such analyses, including technical barriers, privacy restrictions, security concerns, trust issues. Privacy-preserving distributed mining techniques (PPDDM) aim to overcome these challenges by extracting partitioned while minimizing the release information. This paper reports results findings systematic review PPDDM 231 scientific articles published in past 20 years. We summarize state art, compare they address, identify outstanding field. identifies consequence lack standard criteria evaluate new methods proposes comprehensive evaluation with 10 key factors. discuss ambiguous definitions confusion between field, provide suggestions how make clear applicable description techniques. The our enhance understanding applying theoretical real-life use cases, importance involving legal-ethical social experts implementing methods. will serve as helpful guide research future opportunities area PPDDM.