Privacy in Peer-to-Peer Systems

You are identifiable by whom you connect to, not only by what you download.

Last updated on Aug 14, 2026 Research

Project Overview

Discussions of privacy in peer-to-peer systems tended to focus on content: what a user downloads, and who can observe it. This project started from a different place. In BitTorrent, whom you connect to is itself revealing, because people with similar interests end up in the same swarms repeatedly, and those repeated co-occurrences are visible to anyone watching the network.

Working with Luís Amaral’s group at Northwestern, we applied community-detection methods from complex-network analysis to BitTorrent connection patterns. The result, reported in Strange Bedfellows, is that users cluster into stable communities that persist over time and can be recovered from connection structure alone — no payload inspection required. An observer who cannot see what you downloaded can still infer a great deal about what you are interested in, simply from the company you keep.

The interdisciplinary collaboration was essential here: the measurement side supplied the traces and the systems questions, and the network-science side supplied the methods for finding structure in them.

SwarmScreen

If connection patterns are the leak, then the defence has to operate on connection patterns. SwarmScreen adds a controlled fraction of connections to swarms the user has no interest in, deliberately blurring the community structure an observer would otherwise recover.

The design point is plausible deniability rather than concealment. A user’s real activity is still there, but it is no longer separable from behaviour they never chose, so an observer cannot attribute any particular interest with confidence. The cost is a tunable amount of extra traffic, which the tech report examines against the privacy gained.

Software

SwarmScreen — a Vuze extension making downloading behaviour difficult to classify from connection patterns, with a tunable privacy/performance trade-off.