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Targeted advertising involves using a person’s personal data to determine the most promising commercials to show that person. While the benefits are clear, the price paid in terms of loss of privacy may be high. In this work we bridge what seems at first to be contradicting requirements – the ability to personalize data and the need to maintain privacy, especially while reporting back the impressions to the advertiser. We provide two schemes that achieve this, each in its own adversarial model. We put an emphasis on modern TV systems and describe the architecture for supporting it.

PPiTTA - Preserving Privacy in TV Targeted Advertising