Joint optimisation of privacy and cost of in-app mobile user profiling and targeted ads. (arXiv:2011.02959v2 [cs.CR] UPDATED)

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 …

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