Within an inherently stateless Internet ecosystem, E-commerce and e-marketing strategies depend on cross-domain, multi-event online tracking capabilities. Our research thus far has discovered various fraud and risk scenarios associated with HTTP cookie-based tracking systems, and have proposed solutions to mitigate such threats and to improve the robustness of HTTP cookie-based tracking techniques supported by alternative tracking vectors.

Improved tracking capabilities can lead to increased privacy intrusions. Hence, our research explores and proposes privacy-preserving tracking techniques. We present a privacy model that describe the level of privacy intrusion based on information seeking behaviour (ISB) of different categories of applications.

We developed AMNSTE (Affiliate Marketing Network Simulating and Testing Environment), a multi-domain Internet simulation environment that enables us to carry out live experiments. This research was started during my Doctor of Philosophy (PhD) program at Massey University, Albany, Auckland, New Zealand, which was supervised by Assoc. Prof. Anuradha Mathrani and Prof. Chris Scogings. The research finding have been published in following peer-reviewed research publications.

If you wish to have more information or if you wish to contribute to our research project, we would love to hear from you.