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Automated media classification is becoming increasingly common in areas ranging from mobile location recognition to surveillance systems to automated annotation. While these tools can add great value to the public sphere, media searches often process private information; in such situations, it is important to protect the interests of one or both parties. Much attention has been given to the scenario where both the server and the client wish to keep their data secret, but comparatively little work has been done on searches in which only the clients data is sensitive. Nonetheless, there is great potential for applications involving private searches on public databases like Google Images, Flickr, or Wanted Persons directories put forth by various police agencies. In this article, we make the case that one-way private media search is an important and practically viable direction for future research. We will introduce readers to some basic one-way privacy tools and present a case study outlining the design of a private audio search tool on a public database. This case study serves as a backdrop for a discussion on the role of signal processing techniques in the design of privacy-preserving media search systems.