Privacy preserving publication of transactional data

Research output: ThesisDoctoral Thesis

Abstract

Transactional data such as shopping logs, web search queries, and medical notes present enormous opportunities for knowledge discovery through data mining. When such data is published for knowledge discovery however, privacy disclosure risks may arise, making privacy preserving publication a fundamental requirement. While most existing solutions for the privacy preserving publication problem are geared towards structured relational data,very few focus on unstructured data, particularly transactional data. This work explores the existing privacy preserving mechanisms for publishing transactional data, and develops useful and effective new publishing techniques.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Computer and Information Science
  • University of South Australia
Supervisors/Advisors
  • Liu, Jixue, Principal Supervisor, External person
  • Liu, Lin, Co-Supervisor, External person
  • Jiuyong, Li., Principal Supervisor, External person
Place of PublicationAustralia
Publisher
Publication statusPublished - 2017

Fingerprint Dive into the research topics of 'Privacy preserving publication of transactional data'. Together they form a unique fingerprint.

  • Cite this