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DataBank: An Economics Based Privacy Preserving System for Distributing Relevant Advertising and Content

Lukose, Rajan M.; Lillibridge, Mark


Keyword(s): distributed systems; privacy; cryptography; economics; advertising; personalization; search

Abstract: A critical feature of successful new advertising models has been their reliance on knowledge of various types of personal user data in order to make advertisements relevant and useful. This has raised many concerns about privacy and control over personal data. The preservation of privacy would appear to be in direct conflict with the successful new advertising models, which depend on knowledge of personal user data. Here we present a system and its associated advertising model that shows this need not be the case. DataBank is a system for the delivery of relevant advertising (and content more generally) while preserving the privacy of user data as much as possible. The system relies on an economic pricing mechanism, similar in spirit to economic approaches to spam, and a privacy-preserving targeting mechanism in order to achieve relevance. We explicitly consider the possibility of payment of compensation to consumers directly for the piecemeal use of their private data. This variation raises the possibility of users “gaming the system”, a problem for which we provide a novel, efficient cryptographic solution. Notes:

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