A Systematic Review on Privacy-Preserving Distributed Data Mining

Tracking #: 688-1668


Responsible editor: 

Karin Verspoor

Submission Type: 

Survey Paper

Abstract: 

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 metrics to evaluate new PPDDM methods and proposes comprehensive evaluation metrics with 10 key factors. We discuss the ambiguous definitions of privacy and confusion between privacy and security in the field and provide suggestions on 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.

Manuscript: 

Supplementary Files (optional): 

Tags: 

  • Reviewed

Data repository URLs: 

Review results: https://figshare.com/s/cbb2317239ecfa48339f (The dataset is still privately stored in the repository. It will be public when the review paper gets published).

RDF representations of manuscript content: https://raw.githubusercontent.com/data-science-hub/data/master/rdf/ds-rdf-688.ttl

Date of Submission: 

Friday, March 19, 2021

Date of Decision: 

Sunday, May 30, 2021


Nanopublication URLs:

Decision: 

Undecided

Solicited Reviews:


1 Comment

Meta-Review by Editor

The reviewers of your paper have found that your paper addresses an important topic and the survey that you have provided of the relevant literature helps to organise and critique that literature effectively. Further both reviewers appreciated the conclusion that key terms used in the literature are not well-defined. However, they also identified the need for clarity of the methods for identifying and categorising the papers you surveyed, and some additional justification for the specific scope of the review.

Karin Verspoor (https://orcid.org/0000-0002-8661-1544)