Implementation of a data privacy protection tool for transaction data

Daniel Hendry


Supervised by Jianhua Shao; Moderated by Víctor Gutiérrez Basulto

As an increased amount of data being gathered and stored, how to protect the private information contained within such data sets becomes an important issue. One of the recent approach to addressing this issue is called k-anonymisation, which attempts to make any record in a data set identical to at least k-1 other records (hence no individual could be identified). This project aims to implement a software tool based of a version of k-anonymisation in the form of k^m-anonymisation, where this is defined as someone who has partial record knowledge of a record, up to m terms, will not be able to distinguish any record from other k−1 records. This software will be based off an existing algorithm, to help anonymise transaction data. The system is expected to be developed in Java.

Initial Plan (04/02/2019) [Zip Archive]

Final Report (10/05/2019) [Zip Archive]

Publication Form