Bio

Giulia Fanti is a 6th year Ph.D. student at the University of California-Berkeley, studying privacy-preserving algorithms under Professor Kannan Ramchandran. She received her M.S. in EECS from the University of California-Berkeley in 2012 and her B.S. in Electrical and Computer Engineering from Olin College of Engineering in 2010. She is a recipient of the National Science Foundation Graduate Research Fellowship, as well as a Best Paper Award at ACM Sigmetrics 2015 for her work on anonymous rumor spreading, in collaboration with Peter Kairouz, Professor Sewoong Oh and Professor Pramod Viswanath of the University of Illinois at Urbana-Champaign.

Privacy-preserving data access and dissemination; graph signal processing.

Spy vs. Spy: Anonymous Messaging

Anonymous microblogging platforms, such as Secret, Yik Yak, and Whisper have emerged as important tools for sharing one’s thoughts without fear of judgment by friends, the public, or authority figures. These platforms provide anonymity by allowing users to share content (e.g., short messages) with their peers without revealing authorship information to users. However, recent advances in rumor source detection show that existing messaging protocols , including those used in the mentioned anonymous microblogging applications, leak authorship information when the adversary has global access to metadata. For example, if an adversary can see which users of a messaging service received a particular message, or the timestamps at which a subset of users received a given message, the adversary can infer the message author’s identity with high probability. We introduce a novel anonymous messaging protocol, which we call adaptive diffusion, that is designed to resist such adversaries. We show that adaptive diffusion spreads messages quickly while achieving provably-optimal anonymity guarantees when the underlying messaging network is an infinite regular tree. Simulations on real social network data show that adaptive diffusion effectively hides the location of the source even when the graph is finite, irregular and has cycles.