CRSISep 9, 2015

Hiding the Rumor Source

arXiv:1509.02849v243 citations
Originality Highly original
AI Analysis

This addresses the need for anonymity in social media to protect users from judgment or retribution, particularly in authoritarian contexts, though it is incremental as it builds on existing rumor source detection research.

The paper tackles the problem of identifying the source of a rumor in anonymous social media by introducing a novel messaging protocol called adaptive diffusion, which achieves perfect obfuscation of the source on infinite regular trees and effectively hides the source in experiments on a sampled Facebook network.

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 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, 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, irregular and has cycles.

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