Privacy-preserving targeted advertising for mobile devices - Liu, Y (2017)
With the continued proliferation of mobile devices, the collection of information associated with such devices and their users --- such as location, installed applications and cookies associated with built-in browsers --- has become increasingly straightforward. By analysing such information, organisations are often able to deliver more relevant and better focused advertisements. Although such Targeted Mobile Advertising (TMA) offers great benefits to advertisers, it gives rise to a number of concerns, with privacy-related concerns being prominent amongst them. It follows that there is a need for an advertisement-selection mechanism that can support the existing TMA business model in a manner that takes into account consumers' privacy concerns. The research described in this dissertation explores the delicate balance between the goals of the advertisers and the consumers: advertisers pursue profits by applying TMA, which violates consumers' privacy; consumers hope to benefit from useful mobile advertisements without compromising their personal information. The conflicts of interests between consumers and advertisers in the context of targeted mobile advertising brings us to our research question: Is it possible to develop a privacy-preserving TMA framework that enables mobile users to take advantage of useful advertising services without their privacy being compromised, and without impacting significantly advertising effectiveness? In order to answer this question, this dissertation presents four main contributions. First, we report upon the result of a qualitative study to discuss the balance that needs to be struck between privacy and utility in this emerging area. Second, a number of formal models are developed to reason about privacy, as well as to reason about the relationship between privacy and utility in the context of TMA. Third, a novel ad-selection architecture, PPTMA (Privacy-Preserving Targeted Mobile Advertising), is presented and evaluated. Finally, a privacy-preserving advertisement-selection mechanism, AdSelector, is introduced. The mechanism is novel in its combination of a user subscription mechanism, a two-stage ad-selection process, and the application of a trustworthy billing system.