Joint optimisation of privacy and cost of in-app mobile user profiling and targeted ads

by   Imdad Ullah, et al.

Online mobile advertising ecosystems provide advertising and analytics services that collect, aggregate, process and trade rich amount of consumer's personal data and carries out interests-based ads targeting, which raised serious privacy risks and growing trends of users feeling uncomfortable while using internet services. In this paper, we address user's privacy concerns by developing an optimal dynamic optimisation cost-effective framework for preserving user privacy for profiling, ads-based inferencing, temporal apps usage behavioral patterns and interest-based ads targeting. A major challenge in solving this dynamic model is the lack of knowledge of time-varying updates during profiling process. We formulate a mixed-integer optimisation problem and develop an equivalent problem to show that proposed algorithm does not require knowledge of time-varying updates in user behavior. Following, we develop an online control algorithm to solve equivalent problem using Lyapunov optimisation and to overcome difficulty of solving nonlinear programming by decomposing it into various cases and achieve trade-off between user privacy, cost and targeted ads. We carry out extensive experimentations and demonstrate proposed framework's applicability by implementing its critical components using POC `System App'. We compare proposed framework with other privacy protecting approaches and investigate that it achieves better privacy and functionality for various performance parameters.


page 1

page 2

page 3

page 4


Privacy in targeted advertising: A survey

Targeted advertising has transformed the marketing trend for any busines...

Privacy-preserving targeted mobile advertising: A Blockchain-based framework for mobile ads

The targeted advertising is based on preference profiles inferred via re...

Towards a User Privacy-Aware Mobile Gaming App Installation Prediction Model

Over the past decade, programmatic advertising has received a great deal...

Who Would be Interested in Services? An Entity Graph Learning System for User Targeting

With the growing popularity of various mobile devices, user targeting ha...

Preference-Based Privacy Trading

The question we raise through this paper is: Is it economically feasible...

You can't always get what you want: towards user-controlled privacy on Android

Mobile applications (hereafter, apps) collect a plethora of information ...

Reconciling Governmental Use of Online Targeting With Democracy

The societal and epistemological implications of online targeted adverti...

Please sign up or login with your details

Forgot password? Click here to reset