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Anonymous social media platforms, like Secret, Yik Yak, and Whisper, have emerged as important tools for sharing ideas without the fear of judgment. Such anonymous platforms are also important in nations under authoritarian rule, where freedom of expression and the personal safety of message that authors may depend on anonymity. Whether for fear of judgment or retribution, it is sometimes crucial to hide the identities of users who post sensitive messages. In this paper, we consider a global adversary who wishes to identify the author of a message; it observes either a snapshot of the spread of a message at a certain time or sampled timestamp metadata, or both. Recent advances in rumor source detection show that existing messaging protocols are vulnerable against such an adversary. We introduce a novel messaging protocol, which we call adaptive diffusion, and show that under the snapshot adversarial model, adaptive diffusion spreads content fast and achieves perfect obfuscation of the source when the underlying contact network is an infinite regular tree. That is, all users with the message are nearly equally likely to have been the origin of the message. When the contact network is an irregular tree, we characterize the probability of maximum likelihood detection by proving a concentration result over Galton–Watson trees. Experiments on a sampled Facebook network demonstrate that adaptive diffusion effectively hides the location of the source even when the graph is finite, is irregular, and has cycles. [ABSTRACT FROM PUBLISHER]

Web search histories can reveal detailed and sensitive information about people. Private information retrieval (PIR) tackles this potential privacy violation by allowing users to retrieve the wth record of a database without revealing w to the server. However, most known PIR schemes are either very inefficient (and therefore unlikely to gain traction in a practical sense) or reliant on some restrictive assumptions. In this paper, we consider an efficient class of schemes called multi-server PIR. Multi-server PIR assumes that the client communicates with multiple, non-colluding servers, each possessing an identical copy of the database. Significant prior work has gone towards relaxing the anti-collusion assumption, but the literature does not address the assumption that servers store perfectly-synchronized databases. This seems implausible, especially if servers are not meant to collude. We propose the first multi-server PIR scheme to return the desired record even when servers' databases are not perfectly synchronized. Our scheme asymptotically has the same computational and communication complexity as state-of-the-art PIR schemes for synchronized databases; this comes at the expense of probabilistic success and two rounds of communication (most existing schemes require only one). Additionally, this approach efficiently processes multiple concurrent PIR queries. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]